ImageNet classification with deep convolutional neural networks

2017/05/24 by Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton · 2648 citations
Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #Advanced Image Processing Techniques

paper · pdf · doi:10.1145/3065386

Abstract

We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0%, respectively, which is considerably better than the previous state-of-the-art. The neural network, which has 60 million parameters and 650,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully connected layers with a final 1000-way softmax. To make training faster, we used non-saturating neurons and a very efficient GPU implementation of the convolution operation. To reduce overfitting in the fully connected layers we employed a recently developed regularization method called "dropout" that proved to be very effective. We also entered a variant of this model in the ILSVRC-2012 competition and achieved a winning top-5 test error rate of 15.3%, compared to 26.2% achieved by the second-best entry.

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• Learning Quantized Neural Nets by Coarse Gradient Method for Non-linear Classification
• Hands-on Evaluation of Visual Transformers for Object Recognition and Detection
• DirectSwap: Mask-Free Cross-Identity Training and Benchmarking for Expression-Consistent Video Head Swapping
• Microscopic Vehicle Trajectories from Heterogeneous and Area-Based Traffic
• Causality-inspired Single-source Domain Generalization for Medical Image Segmentation
• A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
• Including Image-based Perception in Disturbance Observer for Warehouse Drones
• An Approach for Detection of Entities in Dynamic Media Contents
• Chopper: A Multi-Level GPU Characterization Tool & Derived Insights Into LLM Training Inefficiency
• PR-CapsNet: Pseudo-Riemannian Capsule Network with Adaptive Curvature Routing for Graph Learning
• LayerPipe2: Multistage Pipelining and Weight Recompute via Improved Exponential Moving Average for Training Neural Networks
• On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks
• Fully Convolutional Neural Networks for Dynamic Object Detection in Grid Maps (Masters Thesis)
• Atlas: A Dataset and Benchmark for E-commerce Clothing Product\n Categorization
• Natural-Logarithm-Rectified Activation Function in Convolutional Neural Networks
• PCGAN-CHAR: Progressively Trained Classifier Generative Adversarial Networks for Classification of Noisy Handwritten Bangla Characters
• A Closer Look at Spatiotemporal Convolutions for Action Recognition
• Tackling Graphical NLP problems with Graph Recurrent Networks
• HOLE: Homological Observation of Latent Embeddings for Neural Network Interpretability
• PolSAR Image Classification Based on Dilated Convolution and Pixel-Refining Parallel Mapping network in the Complex Domain
• LVIS: A Dataset for Large Vocabulary Instance Segmentation
• Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework
• Barrier-Free Large-Scale Sparse Tensor Accelerator (BARISTA) For\n Convolutional Neural Networks
• Explaining Deep Neural Networks
• Life is not black and white -- Combining Semi-Supervised Learning with fuzzy labels
• Amulet: Fast TEE-Shielded Inference for On-Device Model Protection
• GlimmerNet: A Lightweight Grouped Dilated Depthwise Convolutions for UAV-Based Emergency Monitoring
• Enhanced Chest Disease Classification Using an Improved CheXNet Framework with EfficientNetV2-M and Optimization-Driven Learning
• Integrating Multi-scale and Multi-filtration Topological Features for Medical Image Classification
• Towards Robust Pseudo-Label Learning in Semantic Segmentation: An Encoding Perspective
• From Forecast to Action: A Deep Learning Model for Predicting Power Outages During Tropical Cyclones
• Hierarchical Deep Learning for Diatom Image Classification: A Multi-Level Taxonomic Approach
• ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
• A Perception CNN for Facial Expression Recognition
• CN-CELEB: a challenging Chinese speaker recognition dataset
• Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response
• Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
• Tensor object classification via multilinear discriminant analysis\n network
• Novel Deep Learning Architectures for Classification and Segmentation of Brain Tumors from MRI Images
• Statistical physics for artificial neural networks
• Towards Hardware-Agnostic Gaze-Trackers
• SPOOF: Simple Pixel Operations for Out-of-Distribution Fooling
• A Comparative Study on Synthetic Facial Data Generation Techniques for Face Recognition
• Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry
• AI & Human Co-Improvement for Safer Co-Superintelligence
• Affine Non-negative Collaborative Representation Based Pattern Classification
• CNN on `Top': In Search of Scalable & Lightweight Image-based Jet Taggers
• TEA: Temporal Excitation and Aggregation for Action Recognition
• On the Effect of Regularization on Nonparametric Mean-Variance Regression
• A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects
• Generative Recursive Reasoning
• ConvSequential-SLAM: A Sequence-based, Training-less Visual Place\n Recognition Technique for Changing Environments
• A Comparative Review of Recent Few-Shot Object Detection Algorithms
• Human-Level Control without Server-Grade Hardware
• TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition
• An all-optical convolutional neural network for image identification
• A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing
• A Cascaded Zoom-In Network for Patterned Fabric Defect Detection
• Rethinking Decoupled Knowledge Distillation: A Predictive Distribution Perspective
• QoSDiff: An Implicit Topological Embedding Learning Framework Leveraging Denoising Diffusion and Adversarial Attention for Robust QoS Prediction
• CASTLE: Regularization via Auxiliary Causal Graph Discovery
• RRPN++: Guidance Towards More Accurate Scene Text Detection
• Performance Evaluation of Transfer Learning Based Medical Image Classification Techniques for Disease Detection
• Bayes-DIC Net: Estimating Digital Image Correlation Uncertainty with Bayesian Neural Networks
• CoDA: From Text-to-Image Diffusion Models to Training-Free Dataset Distillation
• Parameter efficient hybrid spiking-quantum convolutional neural network with surrogate gradient and quantum data-reupload
• Deep Unfolding: Recent Developments, Theory, and Design Guidelines
• On the Binding Problem in Artificial Neural Networks
• Multi-Scale Visual Prompting for Lightweight Small-Image Classification
• What does LIME really see in images?
• Compressed Video Action Recognition with Refined Motion Vector
• Using Deep Learning and Machine Learning to Detect Epileptic Seizure with Electroencephalography (EEG) Data
• Group-Structured Adversarial Training
• Detecting Electric Devices in 3D Images of Bags
• Benchmarking machine learning models for multi-class state recognition in double quantum dot data
• Leveraging Large-Scale Pretrained Spatial-Spectral Priors for General Zero-Shot Pansharpening
• OmniPerson: Unified Identity-Preserving Pedestrian Generation
• Associative Memory using Attribute-Specific Neuron Groups-1: Learning between Multiple Cue Balls
• Breast Cell Segmentation Under Extreme Data Constraints: Quantum Enhancement Meets Adaptive Loss Stabilization
• The brain-AI convergence: Predictive and generative world models for general-purpose computation
• TGDD: Trajectory Guided Dataset Distillation with Balanced Distribution
• Dependency Aware Filter Pruning
• Classification of Radio Signals and HF Transmission Modes with Deep Learning
• Equilibrium Propagation Without Limits
• TPCNet: Triple physical constraints for Low-light Image Enhancement
• Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning
• Multimodal Mixture-of-Experts for ISAC in Low-Altitude Wireless Networks
• Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Visuomotor Policies
• Neural Networks for Predicting Permeability Tensors of 2D Porous Media: Comparison of Convolution- and Transformer-based Architectures
• Deep Learning for Generic Object Detection: A Survey
• Deep learning in neural networks: An overview
• A systematic study of the class imbalance problem in convolutional neural networks
• Masked Autoencoders Are Scalable Vision Learners
• SRM : A Style-based Recalibration Module for Convolutional Neural Networks
• Compact representations of convolutional neural networks via weight\n pruning and quantization
• CrossedWires: A Dataset of Syntactically Equivalent but Semantically\n Disparate Deep Learning Models
• Non-Parametric Neural Style Transfer
• Differentiable Weightless Controllers: Learning Logic Circuits for Continuous Control
• An Introduction to Convolutional Neural Networks
• Directed evolution algorithm drives neural prediction
• Spatiotemporal Satellite Image Downscaling with Transfer Encoders and Autoregressive Generative Models
• Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
• Long-term Temporal Convolutions for Action Recognition
• Emotion Recognition from Speech
• IGen: Scalable Data Generation for Robot Learning from Open-World Images
• Controllable 3D Object Generation with Single Image Prompt
• Scaling Laws for Neural Language Models
• Novelty Detection in MultiClass Scenarios with Incomplete Set of Class Labels
• All-Weather Object Recognition Using Radar and Infrared Sensing
• Dual-Projection Fusion for Accurate Upright Panorama Generation in Robotic Vision
• Designing a Micro-Benchmark Suite to Evaluate gRPC for TensorFlow: Early Experiences
• ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness
• CACARA: Cross-Modal Alignment Leveraging a Text-Centric Approach for Cost-Effective Multimodal and Multilingual Learning
• Structured Context Learning for Generic Event Boundary Detection
• Fixing the train-test resolution discrepancy
• N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras
• BioArc: Discovering Optimal Neural Architectures for Biological Foundation Models
• "Why the face?": Exploring Robot Error Detection Using Instrumented Bystander Reactions
• SelfVIO: Self-supervised deep monocular Visual–Inertial Odometry and depth estimation
• First Steps towards Machine Learning for Prediction and Pre-Correction in Direct Laser Writing
• GhostNet: More Features from Cheap Operations
• Explaining Deep Learning Models for Structured Data using Layer-Wise Relevance Propagation
• Action Recognition with Kernel-based Graph Convolutional Networks
• A Unified Framework for Multi-View Multi-Class Object Pose Estimation
• Bharat Scene Text: A Novel Comprehensive Dataset and Benchmark for Indian Language Scene Text Understanding
• Local and Global Context-and-Object-part-Aware Superpixel-based Data Augmentation for Deep Visual Recognition
• CyCNN: A Rotation Invariant CNN using Polar Mapping and Cylindrical Convolution Layers
• Learning Deep Structure-Preserving Image-Text Embeddings
• CycleCluster: Modernising Clustering Regularisation for Deep Semi-Supervised Classification
• On-the-Job Learning with Bayesian Decision Theory
• CNN-Based Framework for Pedestrian Age and Gender Classification Using Far-View Surveillance in Mixed-Traffic Intersections
• Hybrid Context-Fusion Attention (CFA) U-Net and Clustering for Robust Seismic Horizon Interpretation
• DAONet-YOLOv8: An Occlusion-Aware Dual-Attention Network for Tea Leaf Pest and Disease Detection
• Adversarial Training Towards Robust Multimedia Recommender System
• Adversarial AutoMixup
• Active Learning for GCN-based Action Recognition
• tfShearlab: The TensorFlow Digital Shearlet Transform for Deep Learning
• A Variational View on Bootstrap Ensembles as Bayesian Inference
• Neurodevelopmental Age Estimation of Infants Using a 3D-Convolutional Neural Network Model based on Fusion MRI Sequences
• Neural Networks, Hypersurfaces, and Radon Transforms
• Photo-Realistic Video Prediction on Natural Videos of Largely Changing Frames
• A multi-task convolutional neural network for mega-city analysis using very high resolution satellite imagery and geospatial data
• Provably Powerful Graph Networks
• Tactile-Based Insertion for Dense Box-Packing
• Decoupled Dynamic Filter Networks
• STEP: Segmenting and Tracking Every Pixel
• Underexposed Image Correction via Hybrid Priors Navigated Deep Propagation
• FOSNet: An End-to-End Trainable Deep Neural Network for Scene Recognition
• Fundamentals of Regression
• Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
• BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation
• Mean-Field Limits for Two-Layer Neural Networks Trained with Consensus-Based Optimization
• Differentiable Physics-Neural Models enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations
• A Physics-Informed U-net-LSTM Network for Data-Driven Seismic Response Modeling of Structures
• MorphingDB: A Task-Centric AI-Native DBMS for Model Management and Inference
• Physics-informed neural networks method in high-dimensional integrable systems
• ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
• Generalized Out-of-Distribution Detection: A Survey
• Privacy-Preserving Self-Taught Federated Learning for Heterogeneous Data
• Improving the Generalization of End-to-End Driving through Procedural Generation
• WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection
• Comprehensive Graph-conditional Similarity Preserving Network for Unsupervised Cross-modal Hashing
• Deep Learning Assisted Calibrated Beam Training for Millimeter-Wave Communication Systems
• Guaranteed Optimal Compositional Explanations for Neurons
• Open Vocabulary Compositional Explanations for Neuron Alignment
• CarBench: A Comprehensive Benchmark for Neural Surrogates on High-Fidelity 3D Car Aerodynamics
• On a Sparse Shortcut Topology of Artificial Neural Networks
• Pre-train to Gain: Robust Learning Without Clean Labels
• NNGPT: Rethinking AutoML with Large Language Models
• Back to the Feature: Explaining Video Classifiers with Video Counterfactual Explanations
• Advancing Image Classification with Discrete Diffusion Classification Modeling
• Exo2EgoSyn: Unlocking Foundation Video Generation Models for Exocentric-to-Egocentric Video Synthesis
• Federated Learning in Mobile Edge Networks: A Comprehensive Survey
• Triplet-Based Deep Hashing Network for Cross-Modal Retrieval
• Temporally Distributed Networks for Fast Video Semantic Segmentation
• gradSLAM: Automagically differentiable SLAM
• C³ Framework: An Open-source PyTorch Code for Crowd Counting
• ModHiFi: Identifying High Fidelity predictive components for Model Modification
• IDSplat: Instance-Decomposed 3D Gaussian Splatting for Driving Scenes
• Towards Deep Learning Models Resistant to Adversarial Attacks
• Visual Imitation Made Easy
• Experimental insights into data augmentation techniques for deep learning-based multimode fiber imaging: limitations and success
• Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing
• Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval
• Dynamic Granularity Matters: Rethinking Vision Transformers Beyond Fixed Patch Splitting
• Deep fusion of multi-view and multimodal representation of ALS point cloud for 3D terrain scene recognition
• Towards Biologically Plausible Convolutional Networks
• Multimodal Real-Time Anomaly Detection and Industrial Applications
• Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer
• LookSharp: Attention Entropy Minimization for Test-Time Adaptation
• FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework
• Initializing ReLU networks in an expressive subspace of weights
• Cross-individual Recognition of Emotions by a Dynamic Entropy based on Pattern Learning with EEG features
• A Climatology of Quasi-Linear Convective Systems and Their Hazards in the United States
• Enhanced Center Coding for Cell Detection with Convolutional Neural\n Networks
• RAISECity: A Multimodal Agent Framework for Reality-Aligned 3D World Generation at City-Scale
• FAST: Topology-Aware Frequency-Domain Distribution Matching for Coreset Selection
• Using MLIR Transform to Design Sliced Convolution Algorithm
• Decoupled Audio-Visual Dataset Distillation
• APRIL: Annotations for Policy evaluation with Reliable Inference from LLMs
• The Rapid Growth of AI Foundation Model Usage in Science
• Responses to Critiques on Machine Learning of Criminality Perceptions (Addendum of arXiv:1611.04135)
• Neural Architecture Search without Training
• Separation of time scales and direct computation of weights in deep\n neural networks
• LassoLayer: Nonlinear Feature Selection by Switching One-to-one Links
• Multiple Code Hashing for Efficient Image Retrieval
• PP-YOLO: An Effective and Efficient Implementation of Object Detector
• Spatial-Temporal Dynamic Graph Attention Networks for Ride-hailing Demand Prediction
• Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration
• An End-to-End Approach to Automatic Speech Assessment for Cantonese-speaking People with Aphasia
• Enhancing Adversarial Transferability through Block Stretch and Shrink
• Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path
• Feasibility of Embodied Dynamics Based Bayesian Learning for Continuous Pursuit Motion Control of Assistive Mobile Robots in the Built Environment
• MorphSeek: Fine-grained Latent Representation-Level Policy Optimization for Deformable Image Registration
• Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks
• Automatic Recognition of Coal and Gangue based on Convolution Neural Network
• A Machine Learning-Driven Solution for Denoising Inertial Confinement Fusion Images
• Evolution Strategies at the Hyperscale
• Compositional Explanations of Neurons
• Learning from Noisy Labels with Distillation
• Spatial-Temporal Transformer Networks for Traffic Flow Forecasting
• Learning without Forgetting
• UniFormer: Unifying Convolution and Self-Attention for Visual Recognition
• FVQA: Fact-Based Visual Question Answering
• Network Pruning for Low-Rank Binary Indexing
• Breast Tumor Classification and Segmentation using Convolutional Neural Networks
• CathAI: Fully Automated Interpretation of Coronary Angiograms Using\n Neural Networks
• GLOBE: Accurate and Generalizable PDE Surrogates using Domain-Inspired Architectures and Equivariances
• A Review of Machine Learning for Cavitation Intensity Recognition in Complex Industrial Systems
• Learning to Navigate Using Mid-Level Visual Priors
• What Your Features Reveal: Data-Efficient Black-Box Feature Inversion Attack for Split DNNs
• Med3D: Transfer Learning for 3D Medical Image Analysis
• Task-driven Semantic Coding via Reinforcement Learning
• Incidental Scene Text Understanding: Recent Progresses on ICDAR 2015 Robust Reading Competition Challenge 4
• Syn2Real: Forgery Classification via Unsupervised Domain Adaptation
• A Novel Perspective to Zero-shot Learning: Towards an Alignment of Manifold Structures via Semantic Feature Expansion
• Clustered Object Detection in Aerial Images
• Learning to See Through a Baby's Eyes: Early Visual Diets Enable Robust Visual Intelligence in Humans and Machines
• Sigil: Server-Enforced Watermarking in U-Shaped Split Federated Learning via Gradient Injection
• VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows
• Deep Discriminative Representation Learning with Attention Map for Scene Classification
• SQWA: Stochastic Quantized Weight Averaging for Improving the Generalization Capability of Low-Precision Deep Neural Networks
• XNOR-Net++: Improved Binary Neural Networks
• Towards Optimal Structured CNN Pruning via Generative Adversarial Learning
• DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection for Dual-Energy X-Ray Baggage Imagery
• Convolutional Neural Networks for Large-Scale Remote-Sensing Image Classification
• EVAA—Exchange Vanishing Adversarial Attack on LiDAR Point Clouds in Autonomous Vehicles
• Cross-Learning from Scarce Data via Multi-Task Constrained Optimization
• Hamiltonian Neural Networks
• Learning proofs for the classification of nilpotent semigroups
• Region-Point Joint Representation for Effective Trajectory Similarity Learning
• Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challenge
• Compositional Generalization for Primitive Substitutions
• Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes
• Sequence to Sequence Learning with Neural Networks
• IntPhys: A Benchmark for Visual Intuitive Physics Reasoning
• BinaryConnect: Training Deep Neural Networks with binary weights during propagations
• Questions to Guide the Future of Artificial Intelligence Research
• Recommendation or Discrimination?: Quantifying Distribution Parity in Information Retrieval Systems
• Generic decoding of seen and imagined objects using hierarchical visual features
• Information Theory-Guided Heuristic Progressive Multi-View Coding
• To Click or Not To Click: Automatic Selection of Beautiful Thumbnails from Videos
• Learning a Deep Embedding Model for Zero-Shot Learning
• Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction
• TinyCNN: A Tiny Modular CNN Accelerator for Embedded FPGA
• MineGAN: effective knowledge transfer from GANs to target domains with few images
• A Gaussian Process perspective on Convolutional Neural Networks
• Alpha-Integration Pooling for Convolutional Neural Networks
• Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
• Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation
• LaSOT: A High-quality Large-scale Single Object Tracking Benchmark
• Learning to Hash with Graph Neural Networks for Recommender Systems
• LAYA: Layer-wise Attention Aggregation for Interpretable Depth-Aware Neural Networks
• Sparsity-Control Ternary Weight Networks
• Quaternion Convolutional Neural Networks
• A Survey of Deep Reinforcement Learning in Video Games
• 1st Place Solution for Waymo Open Dataset Challenge -- 3D Detection and Domain Adaptation
• Understanding the robustness of deep neural network classifiers for\n breast cancer screening
• LEA-Net: Layer-wise External Attention Network for Efficient Color Anomaly Detection
• Calibrated Adversarial Training
• Separation and Concentration in Deep Networks
• Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization
• Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
• Balanced Symmetric Cross Entropy for Large Scale Imbalanced and Noisy Data
• DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars
• Credit scoring using neural networks and SURE posterior probability calibration
• Glance-and-Gaze Vision Transformer
• Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics
• Efficient Transfer Bayesian Optimization with Auxiliary Information
• Discovery and Separation of Features for Invariant Representation Learning
• Accelerating Robustness Verification of Deep Neural Networks Guided by Target Labels
• Batch Normalization Preconditioning for Neural Network Training
• Learning Accurate, Comfortable and Human-like Driving
• End-to-End Wireframe Parsing
• Walsh-Hadamard Variational Inference for Bayesian Deep Learning
• Shifted Chunk Transformer for Spatio-Temporal Representational Learning
• Tackling Over-Smoothing for General Graph Convolutional Networks
• Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
• Multi-level Texture Encoding and Representation (MuLTER) based on Deep Neural Networks
• Dense neural networks as sparse graphs and the lightning initialization
• Curriculum Learning: A Survey
• A Comprehensive Overhaul of Feature Distillation
• Can deep learning help you find the perfect match?
• Estimating or Propagating Gradients Through Stochastic Neurons
• HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks
• Differentiable Rendering: A Survey
• Exemplar Loss for Siamese Network in Visual Tracking
• Extremal Contours: Gradient-driven contours for compact visual attribution
• Effective Regularization Through Loss-Function Metalearning
• Deep Image Prior
• Quantile regression with deep ReLU Networks: Estimators and minimax rates
• A study on using image based machine learning methods to develop the surrogate models of stamp forming simulations
• FLClear: Visually Verifiable Multi-Client Watermarking for Federated Learning
• Blow: a single-scale hyperconditioned flow for non-parallel raw-audio\n voice conversion
• Network Moments: Extensions and Sparse-Smooth Attacks
• Global Image Sentiment Transfer
• Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a\n Survey
• Deep Learning Based Defect Detection for Solder Joints on Industrial X-Ray Circuit Board Images
• A Multicollinearity-Aware Signal-Processing Framework for Cross-β Identification via X-ray Scattering of Alzheimer's Tissue
• Multiscale Vision Transformers
• Machine Learning Framework for Efficient Prediction of Quantum Wasserstein Distance
• Learning Straight Flows: Variational Flow Matching for Efficient Generation
• Deep Spatial Pyramid: The Devil is Once Again in the Details
• Generalizing to unseen domains via distribution matching
• Hi-DREAM: Brain Inspired Hierarchical Diffusion for fMRI Reconstruction via ROI Encoder and visuAl Mapping
• Compiling to linear neurons
• The modified Physics-Informed Hybrid Parallel Kolmogorov--Arnold and Multilayer Perceptron Architecture with domain decomposition
• LEMUR: Large scale End-to-end MUltimodal Recommendation
• Physics-informed Machine Learning for Static Friction Modeling in Robotic Manipulators Based on Kolmogorov-Arnold Networks
• AdaptViG: Adaptive Vision GNN with Exponential Decay Gating
• AudioNet: Supervised Deep Hashing for Retrieval of Similar Audio Events
• Classification of motor faults based on transmission coefficient and reflection coefficient of omni-directional antenna using DCNN
• SliderEdit: Continuous Image Editing with Fine-Grained Instruction Control
• Why Should the Server Do It All?: A Scalable, Versatile, and Model-Agnostic Framework for Server-Light DNN Inference over Massively Distributed Clients via Training-Free Intermediate Feature Compression
• Multi-task Learning with Attention for End-to-end Autonomous Driving
• Learning Memory-guided Normality for Anomaly Detection
• Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection
• Unsupervised Domain Expansion from Multiple Sources
• Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and Navigation
• RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion
• Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation
• CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
• A Comprehensive Study of Deep Video Action Recognition
• Convolutional neural networks decode visual stimulus positions from local field potentials on the mouse cortex
• C3AE: Exploring the Limits of Compact Model for Age Estimation
• State-Aware Tracker for Real-Time Video Object Segmentation
• PP-LCNet: A Lightweight CPU Convolutional Neural Network
• ProbSelect: Stochastic Client Selection for GPU-Accelerated Compute Devices in the 3D Continuum
• HipKittens: Fast and Furious AMD Kernels
• Advancing credibility and transparency in brain-to-image reconstruction research: Reanalysis of Koide-Majima, Nishimoto, and Majima (Neural Networks, 2024)
• Privacy Beyond Pixels: Latent Anonymization for Privacy-Preserving Video Understanding
• Quality-Aware Network for Human Parsing
• Integrating Large Circular Kernels into CNNs through Neural Architecture Search
• Under the Skin of Foundation NFT Auctions
• Deep Semantic Hashing with Generative Adversarial Networks
• Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation Learning
• Sample Prior Guided Robust Model Learning to Suppress Noisy Labels
• Edge of chaos as a guiding principle for modern neural network training
• Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search
• AuxBlocks: Defense Adversarial Example via Auxiliary Blocks
• A Hybrid Autoencoder-Transformer Model for Robust Day-Ahead Electricity Price Forecasting under Extreme Conditions
• Minimum Width of Deep Narrow Networks for Universal Approximation
• Learning Performance Optimization for Edge AI System with Time and Energy Constraints
• Refactoring Neural Networks for Verification
• A Survey of Machine Learning Methods and Challenges for Windows Malware Classification
• Inter-Image Communication for Weakly Supervised Localization
• Preparation of Fractal-Inspired Computational Architectures for Advanced Large Language Model Analysis
• Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring and Activation Function
• TopoAct: Visually Exploring the Shape of Activations in Deep Learning
• CBIR using Pre-Trained Neural Networks
• The Low-Rank Simplicity Bias in Deep Networks
• Rethinking Parameter Sharing as Graph Coloring for Structured Compression
• Real-Time Face and Landmark Localization for Eyeblink Detection
• Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
• Escaping the Big Data Paradigm with Compact Transformers
• A Visual Perception-Based Tunable Framework and Evaluation Benchmark for H.265/HEVC ROI Encryption
• QDCNN: Quantum Dilated Convolutional Neural Network
• Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes
• Enhancing Multimodal Misinformation Detection by Replaying the Whole Story from Image Modality Perspective
• One-Shot Knowledge Transfer for Scalable Person Re-Identification
• Radio AGN feedback sustains quiescence only in a minority of massive galaxies
• Global Multiple Extraction Network for Low-Resolution Facial Expression Recognition
• Adversarial Attacks Beyond the Image Space
• Deep Image: Scaling up Image Recognition
• Toward Better Generalization in Few-Shot Learning through the Meta-Component Combination
• Global Context Networks
• Context-aware Learned Mesh-based Simulation via Trajectory-Level Meta-Learning
• NeuroFlex: Column-Exact ANN-SNN Co-Execution Accelerator with Cost-Guided Scheduling
• Beta Distribution Learning for Reliable Roadway Crash Risk Assessment
• Nowcast3D: Reliable precipitation nowcasting via gray-box learning
• Comparative Study of CNN Architectures for Binary Classification of Horses and Motorcycles in the VOC 2008 Dataset
• Accelerating scientific discovery with the common task framework
• Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
• Distribution-Aware Tensor Decomposition for Compression of Convolutional Neural Networks
• Extended Physics Informed Neural Network for Hyperbolic Two-Phase Flow in Porous Media
• Depth-induced NTK: Bridging Over-parameterized Neural Networks and Deep Neural Kernels
• SAAIPAA: Optimizing aspect-angles-invariant physical adversarial attacks on SAR target recognition models
• Joint Optimization of DNN Model Caching and Request Routing in Mobile Edge Computing
• DKN: Deep Knowledge-Aware Network for News Recommendation
• LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
• A novel method for identifying the deep neural network model with the Serial Number
• On Complex Valued Convolutional Neural Networks
• A survey on human-aware robot navigation
• Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
• SinReQ: Generalized Sinusoidal Regularization for Low-Bitwidth Deep\n Quantized Training
• Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images
• Deeper and Wider Siamese Networks for Real-Time Visual Tracking
• SPEC2: SPECtral SParsE CNN Accelerator on FPGAs
• An open access repository of images on plant health to enable the development of mobile disease diagnostics
• Learning with less: label-efficient land cover classification at very high spatial resolution using self-supervised deep learning
• Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning
• MVAFormer: RGB-based Multi-View Spatio-Temporal Action Recognition with Transformer
• Condition Numbers and Eigenvalue Spectra of Shallow Networks on Spheres
• Neural Network Interoperability Across Platforms
• Object Detection as an Optional Basis: A Graph Matching Network for Cross-View UAV Localization
• Automatic Extraction of Road Networks by using Teacher-Student Adaptive Structural Deep Belief Network and Its Application to Landslide Disaster
• Energy-Efficient Deep Learning Without Backpropagation: A Rigorous Evaluation of Forward-Only Algorithms
• HyFormer-Net: A Synergistic CNN-Transformer with Interpretable Multi-Scale Fusion for Breast Lesion Segmentation and Classification in Ultrasound Images
• Parameter Interpolation Adversarial Training for Robust Image Classification
• Diluting Restricted Boltzmann Machines
• Beyond ImageNet: Understanding Cross-Dataset Robustness of Lightweight Vision Models
• Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator
• Image Hashing via Cross-View Code Alignment in the Age of Foundation Models
• Data-Augmented Deep Learning for Downhole Depth Sensing and Field Validation
• ODP-Bench: Benchmarking Out-of-Distribution Performance Prediction
• Exploring Landscapes for Better Minima along Valleys
• Integrating ConvNeXt and Vision Transformers for Enhancing Facial Age Estimation
• Spiking Neural Networks: The Future of Brain-Inspired Computing
• Comparative Analysis of Deep Learning Models for Olive Tree Crown and Shadow Segmentation Towards Biovolume Estimation
• EEG-Driven Image Reconstruction with Saliency-Guided Diffusion Models
• Generative Artificial Intelligence for Air Shower Simulation
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• A Review of AI-Driven Approaches for Nanoscale Heat Conduction and Radiation
• DARTS: A Drone-Based AI-Powered Real-Time Traffic Incident Detection System
• Data-driven discovery of thermal illusions through latent-space geometry
• CHIPSIM: A Co-Simulation Framework for Deep Learning on Chiplet-Based Systems
• VISAT: Benchmarking Adversarial and Distribution Shift Robustness in Traffic Sign Recognition with Visual Attributes
• Feedback Alignment Meets Low-Rank Manifolds: A Structured Recipe for Local Learning
• PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search
• Adversarial Domain Randomization
• Beyond Data Scarcity Optimizing R3GAN for Medical Image Generation from Small Datasets
• Deep Multi-Scale Features Learning for Distorted Image Quality Assessment
• Hybrid Models for Open Set Recognition
• Incremental Methods for Weakly Convex Optimization
• Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey
• Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements
• Winner-Take-All Autoencoders
• Channel Pruning via Optimal Thresholding
• Hypergraph Convolution and Hypergraph Attention
• Deep Learning for Anomaly Detection: A Review
• Person Retrieval in Surveillance Video using Height, Color and Gender
• Medical Concept Representation Learning from Electronic Health Records and its Application on Heart Failure Prediction
• Sharpness-aware Quantization for Deep Neural Networks
• Federated Learning in Mobile Edge Networks: A Comprehensive Survey
• MetaFormer is Actually What You Need for Vision
• Understanding Information Processing in Human Brain by Interpreting Machine Learning Models
• Affinity and Diversity: Quantifying Mechanisms of Data Augmentation
• Deep Learning to Ternary Hash Codes by Continuation
• Camera-aware Proxies for Unsupervised Person Re-Identification
• Joint Object and State Recognition using Language Knowledge
• Twins: Revisiting the Design of Spatial Attention in Vision Transformers
• Deep causal representation learning for unsupervised domain adaptation
• Deep Network Classification by Scattering and Homotopy Dictionary Learning
• Uncertainty-Aware Attention for Reliable Interpretation and Prediction
• A Tandem Learning Rule for Effective Training and Rapid Inference of Deep Spiking Neural Networks
• CNN depth analysis with different channel inputs for Acoustic Scene Classification
• Amadeus: Scalable, Privacy-Preserving Live Video Analytics
• Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition
• Automatic Target Recognition on Synthetic Aperture Radar Imagery: A Survey
• Malleable 2.5D Convolution: Learning Receptive Fields along the Depth-axis for RGB-D Scene Parsing
• Growing a Brain: Fine-Tuning by Increasing Model Capacity
• Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation
• Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
• Adaptive Gradient for Adversarial Perturbations Generation
• Recent Deep Semi-supervised Learning Approaches and Related Works
• Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks
• Deep Learning for the Classification of Lung Nodules
• Deep High-Resolution Representation Learning for Visual Recognition
• Discovering and Explaining the Representation Bottleneck of DNNs
• Face Completion with Semantic Knowledge and Collaborative Adversarial Learning
• MEAL: Multi-Model Ensemble via Adversarial Learning
• Regularizing Explanations in Bayesian Convolutional Neural Networks
• A Spatial-Temporal Decomposition Based Deep Neural Network for Time\n Series Forecasting
• Probabilistic Trust Intervals for Out of Distribution Detection
• Accelerating 3D Deep Learning with PyTorch3D
• Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching
• Neural Network Architectures for Location Estimation in the Internet of Things
• Multi Receptive Field Network for Semantic Segmentation
• Learning Neural Network Classifiers with Low Model Complexity
• Conditional Deep Learning for Energy-Efficient and Enhanced Pattern\n Recognition
• Tango: A Deep Neural Network Benchmark Suite for Various Accelerators
• Rethinking CNN Models for Audio Classification
• Character-level Chinese Writer Identification using Path Signature Feature, DropStroke and Deep CNN
• Voxceleb: Large-scale speaker verification in the wild
• Replay anti-spoofing countermeasure based on data augmentation with post selection
• Learning the Redundancy-free Features for Generalized Zero-Shot Object Recognition
• Gated Channel Transformation for Visual Recognition
• Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon
• Physical Attribute Prediction Using Deep Residual Neural Networks
• Weakly supervised object detection using pseudo-strong labels
• Universal Perturbation Attack Against Image Retrieval
• N-GCN: Multi-scale Graph Convolution for Semi-supervised Node\n Classification
• Temporal-Clustering Invariance in Irregular Healthcare Time Series
• RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for\n Real-Time Point Cloud Shape Completion
• On-Device Machine Learning: An Algorithms and Learning Theory Perspective
• Deep CTR Prediction in Display Advertising
• Dynamic Curriculum Learning for Imbalanced Data Classification
• Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation
• Harnessing Deep Neural Networks with Logic Rules
• Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
• Reclaiming AI as a theoretical tool for cognitive science
• FINCHES: A Computational Framework for Predicting Intermolecular Interactions in Intrinsically Disordered Proteins
• Hyperparameter Search in Machine Learning
• Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset
• Representation Extraction and Deep Neural Recommendation for Collaborative Filtering
• On hyperparameter optimization of machine learning algorithms: Theory and practice
• NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm
• A New Compensatory Genetic Algorithm-Based Method for Effective Compressed Multi-function Convolutional Neural Network Model Selection with Multi-Objective Optimization
• Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
• Dynamic Graph CNN for Learning on Point Clouds
• Global Filter Networks for Image Classification
• ConvMLP: Hierarchical Convolutional MLPs for Vision
• Rethinking the Hyperparameters for Fine-tuning
• Chargrid-OCR: End-to-end Trainable Optical Character Recognition for Printed Documents using Instance Segmentation
• Places: An Image Database for Deep Scene Understanding
• Real World Robustness from Systematic Noise
• Object Detection in 20 Years: A Survey
• Cnns in land cover mapping with remote sensing imagery: a review and meta-analysis
• Open DNN Box by Power Side-Channel Attack
• A Statistician Teaches Deep Learning
• When Follow is Just One Click Away: Understanding Twitter Follow Behavior in the 2016 U.S. Presidential Election
• Adapting Auxiliary Losses Using Gradient Similarity
• A Deep Multi-task Learning Approach to Skin Lesion Classification
• Adaptive Selection of Deep Learning Models on Embedded Systems
• Dual-level Semantic Transfer Deep Hashing for Efficient Social Image Retrieval
• An interpretable deep hierarchical semantic convolutional neural network for lung nodule malignancy classification
• Continual Learning for Robotics: Definition, Framework, Learning\n Strategies, Opportunities and Challenges
• Spotting insects from satellites: modeling the presence of Culicoides\n imicola through Deep CNNs
• MeshingNet: A New Mesh Generation Method based on Deep Learning
• Ingredient-guided multi-modal interaction and refinement network for RGB-D food nutrition assessment
• Data augmentation using learned transformations for one-shot medical image segmentation
• Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks
• AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images
• Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images
• Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent
• CoAtNet: Marrying Convolution and Attention for All Data Sizes
• For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions
• Strategies for Pre-training Graph Neural Networks
• Optimal Feature Transport for Cross-View Image Geo-Localization
• An Efficient Multi-Scale Attention two-stream inflated 3D ConvNet network for cattle behavior recognition
• Shuffled Patch-Wise Supervision for Presentation Attack Detection
• Towards All-around Knowledge Transferring: Learning From Task-irrelevant Labels
• Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks
• Deep Long-Tailed Learning: A Survey
• Batch Group Normalization
• Split Slice Training Augmentation and Hyperparameter Tuning of RAKI\n Networks for Simultaneous Multi-Slice Reconstruction
• Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction
• FlipReID: Closing the Gap between Training and Inference in Person Re-Identification
• Recent Advances in Neural Question Generation
• Efficient Semantic Scene Completion Network with Spatial Group Convolution
• MUREL: Multimodal Relational Reasoning for Visual Question Answering
• Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
• Lifelong Graph Learning
• A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework
• EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction
• Learning Spatiotemporal Features of Ride-sourcing Services with Fusion Convolutional Network
• When Residual Learning Meets Dense Aggregation: Rethinking the Aggregation of Deep Neural Networks
• Global Texture Enhancement for Fake Face Detection in the Wild
• A Simple Semi-Supervised Learning Framework for Object Detection
• FashionBERT: Text and Image Matching with Adaptive Loss for Cross-modal Retrieval
• Deep Residual Learning for Image Recognition
• BigGAN-based Bayesian reconstruction of natural images from human brain activity
• Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings
• HYPER-SNN: Towards Energy-efficient Quantized Deep Spiking Neural Networks for Hyperspectral Image Classification
• Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set
• Does Data Augmentation Benefit from Split BatchNorms
• Recognition of European mammals and birds in camera trap images using deep neural networks
• Do CNNs Encode Data Augmentations?
• Instance-Aware Predictive Navigation in Multi-Agent Environments
• How Transferable are CNN-based Features for Age and Gender\n Classification?
• DeepIris: Iris Recognition Using A Deep Learning Approach
• A system of different layers of abstraction for artificial intelligence
• Learning Optimal Data Augmentation Policies via Bayesian Optimization for Image Classification Tasks
• TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning
• Sentiment Analysis from Images of Natural Disasters
• Distribution Alignment: A Unified Framework for Long-tail Visual Recognition
• Methods for Interpreting and Understanding Deep Neural Networks
• Robust Sparse Linear Discriminant Analysis
• Image Captioning and Visual Question Answering Based on Attributes and External Knowledge
• DiabDeep: Pervasive Diabetes Diagnosis based on Wearable Medical Sensors and Efficient Neural Networks
• The Rise of Radar for Autonomous Vehicles: Signal Processing Solutions and Future Research Directions
• Artificial Intelligence in the Rising Wave of Deep Learning: The Historical Path and Future Outlook [Perspectives]
• Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
• Skeleton-Based Action Recognition With Gated Convolutional Neural Networks
• Perceptual Image Hashing for Content Authentication Based on Convolutional Neural Network With Multiple Constraints
• Omnidirectional Image Quality Assessment by Distortion Discrimination Assisted Multi-Stream Network
• Tensorizing Neural Networks
• GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning
• Meta-Regularization by Enforcing Mutual-Exclusiveness
• Characterizing machine learning process: A maturity framework
• Circumventing Outliers of AutoAugment with Knowledge Distillation
• Information-Theoretic Understanding of Population Risk Improvement with Model Compression
• Bi-stream Pose Guided Region Ensemble Network for Fingertip Localization from Stereo Images
• Fold bifurcation identification through scientific machine learning
• Spectral Signatures in Backdoor Attacks
• A Dataset and Application for Facial Recognition of Individual Gorillas in Zoo Environments
• What makes visual place recognition easy or hard?
• GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
• Deep Residual Dense U-Net for Resolution Enhancement in Accelerated MRI Acquisition
• DANCE: Enhancing saliency maps using decoys
• Competing Ratio Loss for Discriminative Multi-class Image Classification
• How Important is Weight Symmetry in Backpropagation?
• DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
• Learning Robust Representations via Multi-View Information Bottleneck
• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
• Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter
• An Information Theory-inspired Strategy for Automatic Network Pruning
• Detecting COVID-19 from Breathing and Coughing Sounds using Deep Neural\n Networks
• Classification of Pathological and Normal Gait: A Survey
• Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models
• Domain Adaptive SiamRPN++ for Object Tracking in the Wild
• Quantized Adam with Error Feedback
• A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
• Machine Learning Etudes in Conformal Field Theories
• Noise-Sampling Cross Entropy Loss: Improving Disparity Regression Via Cost Volume Aware Regularizer
• Interpretable Deep Convolutional Fuzzy Classifier
• SWNet: Small-World Neural Networks and Rapid Convergence
• O sistema tecnológico digital
• LUTNet: Rethinking Inference in FPGA Soft Logic
• Cloud-based or On-device: An Empirical Study of Mobile Deep Inference
• Modulated binary cliquenet
• And the Bit Goes Down: Revisiting the Quantization of Neural Networks
• Training Deep Nets with Sublinear Memory Cost
• Uformer: A General U-Shaped Transformer for Image Restoration
• Controlling Recurrent Neural Networks by Conceptors
• Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser
• Random neural networks in the infinite width limit as Gaussian processes
• Protein identification with deep learning: from abc to xyz
• Self-Supervised Multi-View Learning via Auto-Encoding 3D Transformations
• A Survey of Deep Learning Approaches for OCR and Document Understanding
• Measuring the Contribution of Multiple Model Representations in\n Detecting Adversarial Instances
• Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia
• Efficient Reservoir Computing using Field Programmable Gate Array and Electro-optic Modulation
• Deep Reinforcement Learning with Quantum-inspired Experience Replay
• Multimodal Emotion Recognition for One-Minute-Gradual Emotion Challenge
• LiftPool: Bidirectional ConvNet Pooling
• SoftTriple Loss: Deep Metric Learning Without Triplet Sampling
• A Real-Time Cross-modality Correlation Filtering Method for Referring Expression Comprehension
• Exclusive: the most-cited papers of the twenty-first century
• Strategies for Conceptual Change in Convolutional Neural Networks
• PIXOR: Real-time 3D Object Detection from Point Clouds
• Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features
• Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations
• Pruning at a Glance: Global Neural Pruning for Model Compression
• Transform-Invariant Convolutional Neural Networks for Image\n Classification and Search
• Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
• Contrastive Multiview Coding
• Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation
• CLCC: Contrastive Learning for Color Constancy
• Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better
• Learning Channel Inter-dependencies at Multiple Scales on Dense Networks for Face Recognition
• VOLO: Vision Outlooker for Visual Recognition
• The Dynamicist Landscape
• CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense
• Multimodal mixing convolutional neural network and transformer for Alzheimer’s disease recognition
• Domain Generalization for Semantic Segmentation: A Survey
• Mitigating Spurious Correlation via Distributionally Robust Learning with Hierarchical Ambiguity Sets
• Self-Supervised Convolutional Subspace Clustering Network
• Stochastic Region Pooling: Make Attention More Expressive
• A Comprehensive Survey of Neural Architecture Search
• GPatt: Fast Multidimensional Pattern Extrapolation with Gaussian Processes
• CDGNet: Class Distribution Guided Network for Human Parsing
• Improving the Authentication with Built-in Camera Protocol Using\n Built-in Motion Sensors: A Deep Learning Solution
• Semi-supervised Domain Adaptation via Minimax Entropy
• Instance Adaptive Self-Training for Unsupervised Domain Adaptation
• Revisiting IM2GPS in the Deep Learning Era
• End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning
• Adaptive Convolutional ELM For Concept Drift Handling in Online Stream Data
• A Survey on Bayesian Deep Learning
• Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing
• Calibration and Consistency of Adversarial Surrogate Losses
• CvS: Classification via Segmentation For Small Datasets
• A Sentiment-and-Semantics-Based Approach for Emotion Detection in Textual Conversations
• Towards Using Count-level Weak Supervision for Crowd Counting
• Unsupervised learning of clutter-resistant visual representations from natural videos
• Driver Drowsiness Detection Model Using Convolutional Neural Networks\n Techniques for Android Application
• Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing
• Multi-Region Ensemble Convolutional Neural Network for Facial Expression Recognition
• Digital Twin: Values, Challenges and Enablers
• On the Importance of Visual Context for Data Augmentation in Scene\n Understanding
• Graph neural networks: A review of methods and applications
• Rotated Feature Network for multi-orientation object detection
• Defending against substitute model black box adversarial attacks with the 01 loss
• Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis
• Noise Contrastive Priors for Functional Uncertainty
• Real-Time Steganalysis for Stream Media Based on Multi-channel Convolutional Sliding Windows
• WSOD²: Learning Bottom-up and Top-down Objectness Distillation for Weakly-supervised Object Detection
• A Battle of Network Structures: An Empirical Study of CNN, Transformer, and MLP
• RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models
• Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics
• Confusing Image Quality Assessment: Toward Better Augmented Reality Experience
• High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
• Generalizing from a Few Examples
• ROAM: Recurrently Optimizing Tracking Model
• The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
• Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design Considerations
• Deep Metric Learning for Practical Person Re-Identification
• Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
• An Image Patch is a Wave: Phase-Aware Vision MLP
• Agriculture-Vision: A Large Aerial Image Database for Agricultural Pattern Analysis
• Any-Precision Deep Neural Networks
• Learning degraded image classification with restoration data fidelity
• Tomato plant disease classification using Multilevel Feature Fusion with adaptive channel spatial and pixel attention mechanism
• High-Performance Large-Scale Image Recognition Without Normalization
• A Semantics-Guided Class Imbalance Learning Model for Zero-Shot\n Classification
• Cross-modal Zero-shot Hashing
• Separating the Effects of Batch Normalization on CNN Training Speed and Stability Using Classical Adaptive Filter Theory
• SurveilEdge: Real-time Video Query based on Collaborative Cloud-Edge Deep Learning
• PAMS: Quantized Super-Resolution via Parameterized Max Scale
• Random VLAD based Deep Hashing for Efficient Image Retrieval
• RGB-based Semantic Segmentation Using Self-Supervised Depth Pre-Training
• Fine-Tuning Models Comparisons on Garbage Classification for Recyclability
• Improving Adversarial Transferability with Gradient Refining
• Generalized Out-of-Distribution Detection: A Survey
• A comprehensive review of object detection with deep learning
• Learning Various Length Dependence by Dual Recurrent Neural Networks
• Universal Lipschitz Approximation in Bounded Depth Neural Networks
• Image Synthesis with a Single (Robust) Classifier
• Symbol Emergence as an Interpersonal Multimodal Categorization
• Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds
• In-domain representation learning for remote sensing
• Deep feature based rice leaf disease identification using support vector machine
• Sequential Graph Convolutional Network for Active Learning
• Performance Analysis and Characterization of Training Deep Learning Models on Mobile Devices
• Vector-quantized Image Modeling with Improved VQGAN
• Adversarial Domain Adaptation with Domain Mixup
• A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities
• Video Modeling with Correlation Networks
• Reversed Active Learning based Atrous DenseNet for Pathological Image Classification
• Usefulness of interpretability methods to explain deep learning based plant stress phenotyping
• PathVQA: 30000+ Questions for Medical Visual Question Answering
• A Kronecker-factored approximate Fisher matrix for convolution layers
• Adaptive Future Frame Prediction with Ensemble Network
• Meta Feature Modulator for Long-tailed Recognition
• Stack-based Buffer Overflow Detection using Recurrent Neural Networks
• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
• Pose-Invariant Embedding for Deep Person Re-Identification
• PlantDoc
• Sim-to-Real Transfer of Robot Learning with Variable Length Inputs
• ActBERT: Learning Global-Local Video-Text Representations
• Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI
• End-to-End Blind Image Quality Assessment Using Deep Neural Networks
• Deep Learning Markov Random Field for Semantic Segmentation
• Post-Training Piecewise Linear Quantization for Deep Neural Networks
• Faster R-CNN: Towards Real-Time Object Detection with Region Proposal\n Networks
• DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition
• Learning with Group Invariant Features: A Kernel Perspective
• Intelligent Autofocus
• QuaterNet: A Quaternion-based Recurrent Model for Human Motion
• LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
• A Simple Pooling-Based Design for Real-Time Salient Object Detection
• LightMOT: Lightweight and anchor-free solution for tracking multiple objects in dense populations
• On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective
• Towards Spatial Variability Aware Deep Neural Networks (SVANN): A\n Summary of Results
• A Deep Neural Network for Audio Classification with a Classifier Attention Mechanism
• Deep High-Resolution Representation Learning for Visual Recognition
• PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
• Improving Description-based Person Re-identification by Multi-granularity Image-text Alignments
• Learning to Localize: A 3D CNN Approach to User Positioning in Massive MIMO-OFDM Systems
• In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
• Material Recognition for Automated Progress Monitoring using Deep Learning Methods
• Data Extraction from Charts via Single Deep Neural Network
• Towards Rapid and Robust Adversarial Training with One-Step Attacks
• Low Precision Floating-point Arithmetic for High Performance FPGA-based CNN Acceleration
• Universal Person Re-Identification
• MAPS: A Synthetic Dataset for Probing Vision Models in a Controlled 3D Scene Space
• ResNet strikes back: An improved training procedure in timm
• Mandarin tone modeling using recurrent neural networks
• Deep Learning in Robotics: A Review of Recent Research
• Searching for A Robust Neural Architecture in Four GPU Hours
• Half and full solar cell efficiency binning by deep learning on electroluminescence images
• Deep Triplet Quantization
• Kernel-Based Smoothness Analysis of Residual Networks
• Toward Intelligent Sensing: Intermediate Deep Feature Compression
• Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks
• Stabilizing DARTS with Amended Gradient Estimation on Architectural Parameters
• Fantastic Four: Differentiable Bounds on Singular Values of Convolution\n Layers
• DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks
• GenURL: A General Framework for Unsupervised Representation Learning
• Artistic Domain Generalisation Methods are Limited by their Deep\n Representations
• Feedback Attention for Cell Image Segmentation
• Dos and Don'ts of Machine Learning in Computer Security
• Attacking and Defending Machine Learning Applications of Public Cloud
• Natural Adversarial Examples
• Decision-based Universal Adversarial Attack
• Branchy-GNN: a Device-Edge Co-Inference Framework for Efficient Point Cloud Processing
• Spatio-temporal masked autoencoder-based phonetic segments classification from ultrasound
• Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework
• MDCNN: A multimodal dual-CNN recursive model for fake news detection via audio- and text-based speech emotion recognition
• Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes
• Can Single Neurons Solve MNIST? The Computational Power of Biological Dendritic Trees
• Improving Object Detection from Scratch via Gated Feature Reuse
• Successive Embedding and Classification Loss for Aerial Image Classification
• In-depth Question classification using Convolutional Neural Networks
• Feature Space Transfer for Data Augmentation
• Going Deeper for Multilingual Visual Sentiment Detection
• SAIA: Split Artificial Intelligence Architecture for Mobile Healthcare System
• Training Robust Deep Neural Networks via Adversarial Noise Propagation
• Salient Instance Segmentation via Subitizing and Clustering
• Deep Modulation Recognition with Multiple Receive Antennas: An End-to-end Feature Learning Approach
• Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems
• Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation
• WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
• ESFNet: Efficient Network for Building Extraction from High-Resolution Aerial Images
• Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey
• A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
• DDcGAN: A Dual-Discriminator Conditional Generative Adversarial Network for Multi-Resolution Image Fusion
• Semantic-Aware Knowledge Preservation for Zero-Shot Sketch-Based Image Retrieval
• Convolutional Neural Network-based Topology Optimization (CNN-TO) By Estimating Sensitivity of Compliance from Material Distribution
• Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective
• How to fine-tune deep neural networks in few-shot learning?
• Exploring the Limits of Language Modeling
• A Comprehensive Survey on Hardware-Aware Neural Architecture Search
• Learning Loss for Test-Time Augmentation
• Improving Network Slimming with Nonconvex Regularization
• Efficient Spatialtemporal Context Modeling for Action Recognition
• Universality of deep convolutional neural networks
• Improved Deep Convolutional Neural Network For Online Handwritten Chinese Character Recognition using Domain-Specific Knowledge
• BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation
• Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers
• Multiresolution Convolutional Autoencoders
• Deep Convolutional Neural Network for Inverse Problems in Imaging
• SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing
• Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria
• Self-training with Noisy Student improves ImageNet classification
• Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure
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• Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images
• BlockDrop: Dynamic Inference Paths in Residual Networks
• When Person Re-identification Meets Changing Clothes
• Deep Facial Expression Recognition: A Survey
• StarGAN v2: Diverse Image Synthesis for Multiple Domains
• Deep Flow Collaborative Network for Online Visual Tracking
• An End-to-End Network for Panoptic Segmentation
• Continual World: A Robotic Benchmark For Continual Reinforcement\n Learning
• Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis
• Orthogonal Gradient Descent for Continual Learning
• Deep Adaptive Wavelet Network
• Bidirectional Mapping Generative Adversarial Networks for Brain MR to PET Synthesis
• A Survey of FPGA-Based Neural Network Accelerator
• Revisiting Self-Supervised Visual Representation Learning
• Deep Quaternion Features for Privacy Protection
• Unsupervised Learning of Invariant Representations in Hierarchical\n Architectures
• Room Geometry Estimation from Room Impulse Responses using Convolutional Neural Networks
• Learning to Hash for Indexing Big Data - A Survey
• CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation
• Zero-shot World Models Are Developmentally Efficient Learners
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• Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
• DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing
• The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation
• Reverse Transfer Learning: Can Word Embeddings Trained for Different NLP\n Tasks Improve Neural Language Models?
• Novel and Effective CNN-Based Binarization for Historically Degraded As-built Drawing Maps
• Multi-label Iterated Learning for Image Classification with Label Ambiguity
• ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
• HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer Faces
• Instance-weighted Central Similarity for Multi-label Image Retrieval
• Pairwise Teacher-Student Network for Semi-Supervised Hashing
• Real-world Mapping of Gaze Fixations Using Instance Segmentation for\n Road Construction Safety Applications
• Stanza: Layer Separation for Distributed Training in Deep Learning
• The OoO VLIW JIT Compiler for GPU Inference
• You Only Look & Listen Once: Towards Fast and Accurate Visual Grounding
• Convergence of a Relaxed Variable Splitting Coarse Gradient Descent\n Method for Learning Sparse Weight Binarized Activation Neural Networks
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• Escoin: Efficient Sparse Convolutional Neural Network Inference on GPUs
• Morphological Network: How Far Can We Go with Morphological Neurons?
• Spatial Pyramid Convolutional Neural Network for Social Event Detection in Static Image
• Data-Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning
• Intelligence Primer
• Salient Facial Features from Humans and Deep Neural Networks
• Enhancing Rotated Object Detection via Anisotropic Gaussian Bounding Box and Bhattacharyya Distance
• S²-MLP: Spatial-Shift MLP Architecture for Vision
• Distilling Image Classifiers in Object Detectors
• Content-Aware Convolutional Neural Networks
• Involution: Inverting the Inherence of Convolution for Visual Recognition
• AQD: Towards Accurate Fully-Quantized Object Detection
• Multi-Target Embodied Question Answering
• PUNCH: Positive UNlabelled Classification based information retrieval in\n Hyperspectral images
• Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks
• Wavelet based edge feature enhancement for convolutional neural networks
• Improving Robustness Without Sacrificing Accuracy with Patch Gaussian\n Augmentation
• Classification of Motor Imagery EEG Signals by Using a Divergence Based Convolutional Neural Network
• Dropout as a Bayesian Approximation: Appendix
• Adaptive Normalized Risk-Averting Training For Deep Neural Networks
• Manipulating Identical Filter Redundancy for Efficient Pruning on Deep and Complicated CNN
• EIRES:Training-free AI-Generated Image Detection via Edit-Induced Reconstruction Error Shift
• DRIP: Dynamic patch Reduction via Interpretable Pooling
• Understanding Convolutional Neural Networks with Information Theory: An Initial Exploration
• Region Comparison Network for Interpretable Few-shot Image Classification
• Detection Defense Against Adversarial Attacks with Saliency Map
• FruitProm: Probabilistic Maturity Estimation and Detection of Fruits and Vegetables
• Corner Proposal Network for Anchor-free, Two-stage Object Detection
• Spatial prediction of apartment rent using regression-based and machine learning-based approaches with a large dataset
• TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation
• Representation Learning: A Review and New Perspectives
• Two-Stream Convolutional Networks for Action Recognition in Videos
• Synergizing chemical and AI communities for advancing laboratories of the future
• Derivation and Analysis of Fast Bilinear Algorithms for Convolution
• Audio-visual Representation Learning for Anomaly Events Detection in Crowds
• Taming Visually Guided Sound Generation
• ResNet: Enabling Deep Convolutional Neural Networks through Residual Learning
• Seeking Salient Facial Regions for Cross-Database Micro-Expression Recognition
• Multi-view Low-rank Preserving Embedding: A Novel Method for Multi-view Representation
• A representer theorem for deep neural networks
• LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
• TAda! Temporally-Adaptive Convolutions for Video Understanding
• Ordinal Pooling Networks: For Preserving Information over Shrinking Feature Maps
• Digital video microscopy enhanced by deep learning
• SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization
• Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations
• Deeply Learned Spectral Total Variation Decomposition
• Deep Learning for EEG motor imagery classification based on multi-layer CNNs feature fusion
• Deeply-learned and spatial–temporal feature engineering for human action understanding
• A backdoor attack against LSTM-based text classification systems
• Explaining Knowledge Distillation by Quantifying the Knowledge
• Image Categorization and Search via a GAT Autoencoder and Representative Models
• Hierarchically Robust Representation Learning
• Learned Dual-View Reflection Removal
• MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers
• Why Do Deep Residual Networks Generalize Better than Deep Feedforward\n Networks? -- A Neural Tangent Kernel Perspective
• PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
• ATP-Net: An Attention-based Ternary Projection Network For Compressed Sensing
• The Benchmarking Epistemology: Construct Validity for Evaluating Machine Learning Models
• Model-Behavior Alignment under Flexible Evaluation: When the Best-Fitting Model Isn't the Right One
• Privacy-Preserving Semantic Communication over Wiretap Channels with Learnable Differential Privacy
• Training a Convolutional Neural Network for Appearance-Invariant Place Recognition
• Common Task Framework For a Critical Evaluation of Scientific Machine Learning Algorithms
• Intrusion Detection: Machine Learning Baseline Calculations for Image\n Classification
• Rethinking Inference Placement for Deep Learning across Edge and Cloud Platforms: A Multi-Objective Optimization Perspective and Future Directions
• Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models
• SeeDNorm: Self-Rescaled Dynamic Normalization
• Deep Learning: A Critical Appraisal
• Multiple Convolutional Features in Siamese Networks for Object Tracking
• Multiclass Burn Wound Image Classification Using Deep Convolutional Neural Networks
• Quanvolutional Neural Networks for Pneumonia Detection: An Efficient Quantum-Assisted Feature Extraction Paradigm
• Quantum Machine Learning for Image Classification: A Hybrid Model of Residual Network with Quantum Support Vector Machine
• Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition
• Top-Down Semantic Refinement for Image Captioning
• Moving Beyond Diffusion: Hierarchy-to-Hierarchy Autoregression for fMRI-to-Image Reconstruction
• TrajGATFormer: A Graph-Based Transformer Approach for Worker and Obstacle Trajectory Prediction in Off-site Construction Environments
• An Improved Analysis of Stochastic Gradient Descent with Momentum
• Attention Residual Fusion Network with Contrast for Source-free Domain Adaptation
• Image Restoration Using Deep Regulated Convolutional Networks
• Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents: Pathways and Paradigms
• From Black-box to Causal-box: Towards Building More Interpretable Models
• Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions
• Task-Adaptive Neural Network Search with Meta-Contrastive Learning
• A Dilated Inception Network for Visual Saliency Prediction
• Widening and Squeezing: Towards Accurate and Efficient QNNs
• EBOP MAVEN: A machine learning model to estimate the input parameters for analytic fitting of detached eclipsing binary light curves
• OpenHype: Hyperbolic Embeddings for Hierarchical Open-Vocabulary Radiance Fields
• Bridging the gap to real-world language-grounded visual concept learning
• 3rd Place Solution to Large-scale Fine-grained Food Recognition
• 3rd Place Solution to ICCV LargeFineFoodAI Retrieval
• FINE Samples for Learning with Noisy Labels
• Parallelization Techniques for Verifying Neural Networks
• Long-tailed Species Recognition in the NACTI Wildlife Dataset
• Evaluating Bayesian Deep Learning Methods for Semantic Segmentation
• One-pixel Signature: Characterizing CNN Models for Backdoor Detection
• Stand-Alone Self-Attention in Vision Models
• Domain Generalization with MixStyle
• Communication-Efficient Federated Distillation
• xMem: A CPU-Based Approach for Accurate Estimation of GPU Memory in Deep Learning Training Workloads
• Graph Neural Regularizers for PDE Inverse Problems
• Memory Constrained Dynamic Subnetwork Update for Transfer Learning
• HybridSOMSpikeNet: A Deep Model with Differentiable Soft Self-Organizing Maps and Spiking Dynamics for Waste Classification
• Pose Augmentation: Class-agnostic Object Pose Transformation for Object Recognition
• A Semantic Loss Function for Deep Learning with Symbolic Knowledge
• Anderson-type acceleration method for Deep Neural Network optimization
• SAG-GAN: Semi-Supervised Attention-Guided GANs for Data Augmentation on Medical Images
• Machine learning identification of fractional-order vortex beam diffraction process
• Rethinking Cross-lingual Gaps from a Statistical Viewpoint
• Attentive Convolution: Unifying the Expressivity of Self-Attention with Convolutional Efficiency
• Stealing Neural Networks via Timing Side Channels
• Better Tokens for Better 3D: Advancing Vision-Language Modeling in 3D Medical Imaging
• TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning
• Advances in Inference and Representation for Simultaneous Localization\n and Mapping
• ARC: A Vision-based Automatic Retail Checkout System
• Spatial Attention Point Network for Deep-learning-based Robust Autonomous Robot Motion Generation
• On the Power Saving in High-Speed Ethernet-based Networks for Supercomputers and Data Centers
• Study of Training Dynamics for Memory-Constrained Fine-Tuning
• BrainCognizer: Brain Decoding with Human Visual Cognition Simulation for fMRI-to-Image Reconstruction
• Precise classification of low quality G-banded Chromosome Images by reliability metrics and data pruning classifier
• Entity Embeddings of Categorical Variables
• A Semi-Parametric Estimation Method for the Quantile Spectrum with an Application to Earthquake Classification Using Convolutional Neural Network
• Layer-Parallel Training of Deep Residual Neural Networks
• Accelerated WGAN update strategy with loss change rate balancing
• A Unified Perspective on Optimization in Machine Learning and Neuroscience: From Gradient Descent to Neural Adaptation
• Lipschitz regularity of deep neural networks: analysis and efficient estimation
• Data-Driven Short-Term Voltage Stability Assessment Based on Spatial-Temporal Graph Convolutional Network
• Image augmentation with invertible networks in interactive satellite image change detection
• Visual Space Optimization for Zero-shot Learning
• Skin Cancer Recognition using Deep Residual Network
• Data-Driven Analysis of Intersectional Bias in Image Classification: A Framework with Bias-Weighted Augmentation
• Rethinking ResNets: Improved Stacking Strategies With High Order Schemes
• Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey
• End-to-End Spoken Language Translation
• Towards In-Situ Failure Assessment: Deep Learning on DIC Results for Laminated Composites
• Large batch size training of neural networks with adversarial training and second-order information
• Learning from N-Tuple Data with M Positive Instances: Unbiased Risk Estimation and Theoretical Guarantees
• Deep Learning-Based Human Pose Estimation: A Survey
• MCANet: A Coherent Multimodal Collaborative Attention Network for Advanced Modulation Recognition in Adverse Noisy Environments
• BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
• Application of Deep Neural Networks to assess corporate Credit Rating
• Decoding Dynamic Visual Experience from Calcium Imaging via Cell-Pattern-Aware Pretraining
• Provable Generalization Bounds for Deep Neural Networks with Momentum-Adaptive Gradient Dropout
• FreqPDE: Rethinking Positional Depth Embedding for Multi-View 3D Object Detection Transformers
• Deep Photovoltaic Nowcasting
• Modeling and Analysis of Energy Harvesting and Smart Grid-Powered Wireless Communication Networks: A Contemporary Survey
• Swin Transformer V2: Scaling Up Capacity and Resolution
• An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity
• Morphology-Aware KOA Classification: Integrating Graph Priors with Vision Models
• Automatic Classification of Circulating Blood Cell Clusters based on Multi-channel Flow Cytometry Imaging
• DRAMNet: Authentication based on Physical Unique Features of DRAM Using Deep Convolutional Neural Networks
• UMIche: A UMI-centric analysis platform for enhancing molecular quantification accuracy in bulk and single-cell sequencing
• Becoming episodic: The Development of Objectivity
• Application of CNN to a fine segmented scintillator detector for a single particle and neutrino-nucleon event
• Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies
• Semantic-E2VID: a Semantic-Enriched Paradigm for Event-to-Video Reconstruction
• Symmetries in PAC-Bayesian Learning
• End-to-end Phoneme Sequence Recognition using Convolutional Neural\n Networks
• Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising
• Themis: Fair and Efficient GPU Cluster Scheduling
• Fine-tuning Flow Matching Generative Models with Intermediate Feedback
• WP-CrackNet: A Collaborative Adversarial Learning Framework for End-to-End Weakly-Supervised Road Crack Detection
• Exploring Structural Degradation in Dense Representations for Self-supervised Learning
• Guiding Query Position and Performing Similar Attention for Transformer-Based Detection Heads
• View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
• ArmFormer: Lightweight Transformer Architecture for Real-Time Multi-Class Weapon Segmentation and Classification
• RSG: A Simple but Effective Module for Learning Imbalanced Datasets
• PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python
• FOX-NAS: Fast, On-device and Explainable Neural Architecture Search
• AUGUSTUS: An LLM-Driven Multimodal Agent System with Contextualized User Memory
• Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training
• Moment-Based Domain Adaptation: Learning Bounds and Algorithms
• Rebooting Neuromorphic Hardware Design -- A Complexity Engineering Approach
• OpenEDS: Open Eye Dataset
• A deep learning approach to detecting volcano deformation from satellite\n imagery using synthetic datasets
• Video Swin Transformer
• CodeNet: Training Large Scale Neural Networks in Presence of Soft-Errors
• ELASTIC: Improving CNNs with Dynamic Scaling Policies
• Deep Variable-Block Chain with Adaptive Variable Selection
• Video-based Human Action Recognition using Deep Learning: A Review
• VM-BeautyNet: A Synergistic Ensemble of Vision Transformer and Mamba for Facial Beauty Prediction
• Deep generative priors for 3D brain analysis
• SimNets: A Generalization of Convolutional Networks
• A solution to generalized learning from small training sets found in infant repeated visual experiences of individual objects
• From Pixels to Words -- Towards Native Vision-Language Primitives at Scale
• Multi-modal video data-pipelines for machine learning with minimal human supervision
• Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling
• Tutorial on Variational Autoencoders
• Semantic representations emerge in biologically inspired ensembles of cross-supervising neural networks
• A Multi-domain Image Translative Diffusion StyleGAN for Iris Presentation Attack Detection
• Synergistic Integration and Discrepancy Resolution of Contextualized Knowledge for Personalized Recommendation
• Efficient Learning of Distributed Linear-Quadratic Controllers
• MUSE: Model-based Uncertainty-aware Similarity Estimation for zero-shot 2D Object Detection and Segmentation
• On the expressivity of sparse maxout networks
• Composition-based Multi-Relational Graph Convolutional Networks
• Scaling Vision Transformers for Functional MRI with Flat Maps
• DeDelayed: Deleting Remote Inference Delay via On-Device Correction
• Graph Neural Networks: A Review of Methods and Applications
• Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study
• Accelerating Federated Learning via Momentum Gradient Descent
• O3BNN-R: An Out-of-Order Architecture for High-Performance and Regularized BNN Inference
• Multi-Agent Design Assistant for the Simulation of Inertial Fusion Energy
• Feature Denoising for Improving Adversarial Robustness
• The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research
• Use of covariance matrix images for electroencephalography signal classification for multiclass motor imagery‐based brain computer interface
• Multi-Scale High-Resolution Logarithmic Grapher Module for Efficient Vision GNNs
• Randomness and Interpolation Improve Gradient Descent
• Plant leaf disease classification using EfficientNet deep learning model
• Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization
• Layer Normalization
• Visual7W: Grounded Question Answering in Images
• AnyUp: Universal Feature Upsampling
• GenCellAgent: Generalizable, Training-Free Cellular Image Segmentation via Large Language Model Agents
• Feature extraction of machine learning and phase transition point of\n Ising model
• Convolution, attention and structure embedding
• A Regularized Convolutional Neural Network for Semantic Image Segmentation
• Cautious Weight Decay
• MetaFormer Is Actually What You Need for Vision
• Metronome: Efficient Scheduling for Periodic Traffic Jobs with Network and Priority Awareness
• Local Background Features Matter in Out-of-Distribution Detection
• Revisiting Meta-Learning with Noisy Labels: Reweighting Dynamics and Theoretical Guarantees
• SDGraph: Multi-Level Sketch Representation Learning by Sparse-Dense Graph Architecture
• Faster Meta Update Strategy for Noise-Robust Deep Learning
• Tackling Catastrophic Forgetting and Background Shift in Continual Semantic Segmentation
• Robustness May Be at Odds with Accuracy
• Unsupervised Learning of Object Keypoints for Perception and Control
• Harnessing the Vulnerability of Latent Layers in Adversarially Trained\n Models
• R-Drop: Regularized Dropout for Neural Networks
• Lightweight CNN-Based Wi-Fi Intrusion Detection Using 2D Traffic Representations
• Cross Domain Image Matching in Presence of Outliers
• Fault Localization with Code Coverage Representation Learning
• Hierarchical Qubit-Merging Transformer for Quantum Error Correction
• High-resolution Photo Enhancement in Real-time: A Laplacian Pyramid Network
• Scalable Primitives for Generalized Sensor Fusion in Autonomous Vehicles
• Identification of tea foliar diseases and pest damage under practical field conditions using a convolutional neural network
• An Overview of Attacks and Defences on Intelligent Connected Vehicles
• Generating Binary Tags for Fast Medical Image Retrieval Based on Convolutional Nets and Radon Transform
• Adversarial Invariant Feature Learning with Accuracy Constraint for Domain Generalization
• Text-Enhanced Panoptic Symbol Spotting in CAD Drawings
• Source-Free Object Detection with Detection Transformer
• NeuroSwift: A Lightweight Cross-Subject Framework for fMRI Visual Reconstruction of Complex Scenes
• Weeping and Gnashing of Teeth: Teaching Deep Learning in Image and Video Processing Classes
• PERMDNN: Efficient Compressed DNN Architecture with Permuted Diagonal\n Matrices
• ΔEnergy: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization
• Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form Solution
• Statistical Guarantees for High-Dimensional Stochastic Gradient Descent
• A compressed code for memory discrimination
• Restricted Receptive Fields for Face Verification
• dN/dx Reconstruction with Deep Learning for High-Granularity TPCs
• High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator
• A Strategy of MR Brain Tissue Images' Suggestive Annotation Based on Modified U-Net
• Deep learning methods based on cross-section images for predicting\n effective thermal conductivity of composites
• Learning the mapping x↦ ∑_i=1^d x_i²: the cost of finding the needle in a haystack
• GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer
• Can a powerful neural network be a teacher for a weaker neural network?
• CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU
• Distributed Learning of Deep Neural Networks using Independent Subnet Training
• Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
• Sketch Animation: State-of-the-art Report
• Understanding Notions of Stationarity in Non-Smooth Optimization
• A Large-Scale Benchmark for Food Image Segmentation
• Deep Learning using Linear Support Vector Machines
• Translution: Unifying Self-attention and Convolution for Adaptive and Relative Modeling
• Local-Global Context-Aware and Structure-Preserving Image Super-Resolution
• Automated Glaucoma Report Generation via Dual-Attention Semantic Parallel-LSTM and Multimodal Clinical Data Integration
• Stochastic Training is Not Necessary for Generalization
• Prismo: A Decision Support System for Privacy-Preserving ML Framework Selection
• Machine learning in ant biology research: A systematic review
• Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images
• Small is Sufficient: Reducing the World AI Energy Consumption Through Model Selection
• Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies
• Computer-aided diagnosis of endobronchial ultrasound images using convolutional neural network
• Self-taught Object Localization with Deep Networks
• Understanding Character Recognition using Visual Explanations Derived from the Human Visual System and Deep Networks
• SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition
• DeepHash: Getting Regularization, Depth and Fine-Tuning Right
• Piecewise Linear Units Improve Deep Neural Networks
• OR-Net: Pointwise Relational Inference for Data Completion under Partial Observation
• CAMAL: Context-Aware Multi-layer Attention framework for Lightweight Environment Invariant Visual Place Recognition
• Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions
• Architecture Induces Structural Invariant Manifolds of Neural Network Training Dynamics
• Deep prior-based denoising for state-of-the-art scientific imaging and metrology
• Needles in Haystacks: On Classifying Tiny Objects in Large Images
• Drill the Cork of Information Bottleneck by Inputting the Most Important Data
• SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
• Fully Convolutional Networks for Semantic Segmentation
• AS-MLP: An Axial Shifted MLP Architecture for Vision
• Learning Transferable Adversarial Examples via Ghost Networks
• AGDC: Automatic Garbage Detection and Collection
• Provable Watermarking for Data Poisoning Attacks
• Distributionally robust approximation property of neural networks
• Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models
• Integrating Specialized Classifiers Based on Continuous Time Markov Chain
• MAT-Agent: Adaptive Multi-Agent Training Optimization
• MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1 error rate. Ensembles overview and proposal
• VirDA: Reusing Backbone for Unsupervised Domain Adaptation with Visual Reprogramming
• Self-Training With Noisy Student Improves ImageNet Classification
• RAVEN: A Dataset for Relational and Analogical Visual rEasoNing
• LieTransformer: Equivariant self-attention for Lie Groups
• Exploring Data Aggregation and Transformations to Generalize across Visual Domains
• Image Classification with Classic and Deep Learning Techniques
• The impact of abstract and object tags on image privacy classification
• DISCO: Diversifying Sample Condensation for Efficient Model Evaluation
• Deep Neural Networks Inspired by Differential Equations
• C-Net: A Reliable Convolutional Neural Network for Biomedical Image Classification
• Exploring Modality-shared Appearance Features and Modality-invariant Relation Features for Cross-modality Person Re-Identification
• DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing from Decentralised Data
• Rectifier Neural Network with a Dual-Pathway Architecture for Image Denoising
• Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians
• Joint Architecture and Knowledge Distillation in CNN for Chinese Text Recognition
• Sparse components distinguish visual pathways & their alignment to neural networks
• TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices
• What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors
• SGAS: Sequential Greedy Architecture Search
• Representation Learning from Limited Educational Data with Crowdsourced Labels
• Evaluation of Model Selection for Kernel Fragment Recognition in Corn Silage
• Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art
• Time-Frequency Analysis based Blind Modulation Classification for Multiple-Antenna Systems
• AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results
• Learning Longterm Representations for Person Re-Identification Using Radio Signals
• A Unified Object Motion and Affinity Model for Online Multi-Object Tracking
• Temporal Accumulative Features for Sign Language Recognition
• Long-Tailed Recognition via Information-Preservable Two-Stage Learning
• Quick-CapsNet (QCN): A fast alternative to Capsule Networks
• Artificial Hippocampus Networks for Efficient Long-Context Modeling
• Label-frugal satellite image change detection with generative virtual exemplar learning
• Interactive reconstruction of Monte Carlo image sequences using a recurrent denoising autoencoder
• The dilemma of quantum neural networks
• Dataset Reuse: Toward Translating Principles to Practice
• A review of evolving remote sensing and automated techniques in rock glacier mapping
• ImageNet Large Scale Visual Recognition Challenge
• Random Erasing Data Augmentation
• CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices
• Rapid computation of high-level visual surprise
• SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems
• Verifying Memoryless Sequential Decision-making of Large Language Models
• Associative Memory Model with Neural Networks: Memorizing multiple images with one neuron
• Shaken or Stirred? An Analysis of MetaFormer's Token Mixing for Medical Imaging
• TreeNet: Layered Decision Ensembles
• Riddled basin geometry sets fundamental limits to predictability and reproducibility in deep learning
• Multi-task Neural Networks for QSAR Predictions
• Learning the detector in optical tomography
• Computing frustration and near-monotonicity in deep neural networks
• Evaluation of fish feeding intensity in aquaculture using a convolutional neural network and machine vision
• Neuroplastic Modular Framework: Cross-Domain Image Classification of Garbage and Industrial Surfaces
• Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation
• Visual Representations inside the Language Model
• Bridging Reasoning to Learning: Unmasking Illusions using Complexity Out of Distribution Generalization
• Improving Large-Scale Recommender Systems with Auxiliary Learning
• Exploring the Efficacy of Modified Transfer Learning in Identifying Parkinson's Disease Through Drawn Image Patterns
• POMO: Policy Optimization with Multiple Optima for Reinforcement Learning
• Improving Transferability of Adversarial Examples with Input Diversity
• Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps
• Continuous vs. Discrete Optimization of Deep Neural Networks
• FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation
• Multi-Scale Aligned Distillation for Low-Resolution Detection
• A Mathematical Explanation of Transformers for Large Language Models and GPTs
• Using predefined vector systems as latent space configuration for neural network supervised training on data with arbitrarily large number of classes
• Attention Branch Network: Learning of Attention Mechanism for Visual Explanation
• Quantization Range Estimation for Convolutional Neural Networks
• Interpolated Convolutional Networks for 3D Point Cloud Understanding
• ConvBERT: Improving BERT with Span-based Dynamic Convolution
• Evaluation of Transfer Learning for Classification of: (1) Diabetic\n Retinopathy by Digital Fundus Photography and (2) Diabetic Macular Edema,\n Choroidal Neovascularization and Drusen by Optical Coherence Tomography
• End-to-end Active Object Tracking via Reinforcement Learning
• Generation and Comprehension of Unambiguous Object Descriptions
• Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers
• Task-Level Contrastiveness for Cross-Domain Few-Shot Learning
• HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion
• Conditional Pseudo-Supervised Contrast for Data-Free Knowledge Distillation
• Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification
• Accuracy Law for the Future of Deep Time Series Forecasting
• Hyperparameter Loss Surfaces Are Simple Near their Optima
• Using Fourier Analysis and Mutant Clustering to Accelerate DNN Mutation Testing
• Visual Language Model as a Judge for Object Detection in Industrial Diagrams
• An Efficient Quality Metric for Video Frame Interpolation Based on Motion-Field Divergence
• Image Generation Based on Image Style Extraction
• Real-time Hand Gesture Detection and Classification Using Convolutional\n Neural Networks
• Fast Object Detection in Compressed Video
• Phase Collaborative Network for Two-Phase Medical Image Segmentation
• TextCAM: Explaining Class Activation Map with Text
• GLAI: GreenLightningAI for Accelerated Training through Knowledge Decoupling
• Latency-Aware Differentiable Neural Architecture Search
• Realization of spatial sparseness by deep ReLU nets with massive data
• Indices Matter: Learning to Index for Deep Image Matting
• Semantic Visual Simultaneous Localization and Mapping: A Survey on State of the Art, Challenges, and Future Directions
• AWAC: Accelerating Online Reinforcement Learning with Offline Datasets
• Max-Pooling Dropout for Regularization of Convolutional Neural Networks
• Hessian-Aware Pruning and Optimal Neural Implant
• Robust Context-Aware Object Recognition
• Signal Classification Recovery Across Domains Using Unsupervised Domain Adaptation
• Assessing Foundation Models for Mold Colony Detection with Limited Training Data
• Quantum Probabilistic Label Refining: Enhancing Label Quality for Robust Image Classification
• FourPhonon_GPU: A GPU-accelerated framework for calculating phonon scattering rates and thermal conductivity
• Uformer: A General U-Shaped Transformer for Image Restoration
• Digital Passport: A Novel Technological Strategy for Intellectual Property Protection of Convolutional Neural Networks
• Normal-Abnormal Guided Generalist Anomaly Detection
• On-the-Fly Data Augmentation via Gradient-Guided and Sample-Aware Influence Estimation
• Advances in Medical Image Segmentation: A Comprehensive Survey with a Focus on Lumbar Spine Applications
• Finding beans in burgers: Deep semantic-visual embedding with\n localization
• PointConv: Deep Convolutional Networks on 3D Point Clouds
• DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
• PhraseStereo: The First Open-Vocabulary Stereo Image Segmentation Dataset
• On zero-shot recognition of generic objects
• Time-series forecasting with deep learning: a survey
• Deep Neural Networks are Easily Fooled: High Confidence Predictions for\n Unrecognizable Images
• From Videos to Indexed Knowledge Graphs -- Framework to Marry Methods for Multimodal Content Analysis and Understanding
• Beyond the Memory Wall: A Case for Memory-centric HPC System for Deep\n Learning
• FARSA: Fully Automated Roadway Safety Assessment
• Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling
• AIRCHITECT: Learning Custom Architecture Design and Mapping Space
• Benchmarking Deep Learning Convolutions on Energy-constrained CPUs
• From MNIST to ImageNet: Understanding the Scalability Boundaries of Differentiable Logic Gate Networks
• The Impact of Scaling Training Data on Adversarial Robustness
• Sharpness of Minima in Deep Matrix Factorization: Exact Expressions
• Using Images from a Video Game to Improve the Detection of Truck Axles
• Effective Model Pruning
• Hybrid Dual-Batch and Cyclic Progressive Learning for Efficient Distributed Training
• AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs
• Human vs. AI Safety Perception? Decoding Human Safety Perception with Eye-Tracking Systems, Street View Images, and Explainable AI
• Spontaneous High-Order Generalization in Neural Theory-of-Mind Networks
• Accelerating Dynamic Image Graph Construction on FPGA for Vision GNNs
• Symmetry-Aware Bayesian Optimization via Max Kernels
• CLASP: Adaptive Spectral Clustering for Unsupervised Per-Image Segmentation
• Automatic recognition of feeding and foraging behaviour in pigs using deep learning
• ThermalGen: Style-Disentangled Flow-Based Generative Models for RGB-to-Thermal Image Translation
• Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers
• Enabling Physical AI through Biological Principles
• Specialization after Generalization: Towards Understanding Test-Time Training in Foundation Models
• DRIFT: Divergent Response in Filtered Transformations for Robust Adversarial Defense
• PEARL: Performance-Enhanced Aggregated Representation Learning
• Towards Foundation Models for Cryo-ET Subtomogram Analysis
• High-Order Progressive Trajectory Matching for Medical Image Dataset Distillation
• BALF: Budgeted Activation-Aware Low-Rank Factorization for Fine-Tuning-Free Model Compression
• What Are We Automating? On the Need for Vision and Expertise When Deploying AI Systems
• Plant3R: Fusing 3D feature learning with Gaussian splatting to enhance wheat plant 3D reconstruction precision
• MLPerf Training Benchmark
• Learning to Diversify for Single Domain Generalization
• The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration
• Model Watermarking for Image Processing Networks
• A Consolidated Approach to Convolutional Neural Networks and the Kolmogorov Complexity
• Retrieve-Then-Adapt: Example-based Automatic Generation for Proportion-related Infographics
• Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding
• Exploring Uncertainty in Deep Learning for Construction of Prediction Intervals
• Semantically-Aware Strategies for Stereo-Visual Robotic Obstacle Avoidance
• Tent: Fully Test-time Adaptation by Entropy Minimization
• LifeCLEF Plant Identification Task 2014
• LifeCLEF Plant Identification Task 2014
• Gradient Flow Convergence Guarantee for General Neural Network Architectures
• FairViT-GAN: A Hybrid Vision Transformer with Adversarial Debiasing for Fair and Explainable Facial Beauty Prediction
• Influence-Guided Concolic Testing of Transformer Robustness
• Towards Interpretable Visual Decoding with Attention to Brain Representations
• A Computational Perspective on NeuroAI and Synthetic Biological Intelligence
• Spatially Parallel All-optical Neural Networks
• QuadEnhancer: Leveraging Quadratic Transformations to Enhance Deep Neural Networks
• Model-agnostic interpretation by visualization of feature perturbations
• Probabilistic Bearing Fault Diagnosis Using Gaussian Process with Tailored Feature Extraction
• Deep Learning Approaches with Explainable AI for Differentiating Alzheimer Disease and Mild Cognitive Impairment
• The unbearable slowness of being: Why do we live at 10 bits/s?
• Machine learning for synthetic gene circuit engineering
• Foundation models in bioinformatics
• Patch Rebirth: Toward Fast and Transferable Model Inversion of Vision Transformers
• Sparse, Collaborative, or Nonnegative Representation: Which Helps Pattern Classification?
• Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension
• Program-Guided Image Manipulators
• Metric-based Regularization and Temporal Ensemble for Multi-task\n Learning using Heterogeneous Unsupervised Tasks
• Stochastic Interpolants via Conditional Dependent Coupling
• HTMA-Net: Towards Multiplication-Avoiding Neural Networks via Hadamard Transform and In-Memory Computing
• DPFNAS: Differential Privacy-Enhanced Federated Neural Architecture Search for 6G Edge Intelligence
• Learning Modulated Loss for Rotated Object Detection
• Learning Generalizable Visual Representations via Interactive Gameplay
• CProp: Adaptive Learning Rate Scaling from Past Gradient Conformity
• On Controlled DeEntanglement for Natural Language Processing
• Deep Learning for Oral Health: Benchmarking ViT, DeiT, BEiT, ConvNeXt, and Swin Transformer
• Adaptive and Iteratively Improving Recurrent Lateral Connections
• How Secure is Distributed Convolutional Neural Network on IoT Edge Devices?
• Targeted perturbations reveal brain-like local coding axes in robustified, but not standard, ANN-based brain models
• A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks
• MindCraft: How Concept Trees Take Shape In Deep Models
• PAPER: Privacy-Preserving Convolutional Neural Networks using Low-Degree Polynomial Approximations and Structural Optimizations on Leveled FHE
• Survey of Machine Learning Accelerators
• IONext: Unlocking the Next Era of Inertial Odometry
• A Sparse CNN Accelerator for Eliminating Redundant Computations in Intra- and Inter-Convolutional/Pooling Layers
• TSDM: Tracking by SiamRPN++ with a Depth-refiner and a Mask-generator
• Comparison and Benchmarking of AI Models and Frameworks on Mobile Devices
• Generative Image Modeling Using Spatial LSTMs
• Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks
• Visual Relationship Detection using Scene Graphs: A Survey
• Restructuring Batch Normalization to Accelerate CNN Training
• Mining Domain Knowledge: Improved Framework towards Automatically Standardizing Anatomical Structure Nomenclature in Radiotherapy
• A Learning-from-noise Dilated Wide Activation Network for denoising Arterial Spin Labeling (ASL) Perfusion Images
• On Embeddings in Relational Databases
• deepSELF: An Open Source Deep Self End-to-End Learning Framework
• Reconstructed spatial receptive field structures by reverse correlation technique explains the visual feature selectivity of units in deep convolutional neural networks
• SocialAI 0.1: Towards a Benchmark to Stimulate Research on Socio-Cognitive Abilities in Deep Reinforcement Learning Agents
• Design of Reconfigurable Multi-Operand Adder for Massively Parallel\n Processing
• Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning
• Progressive Weight Loading: Accelerating Initial Inference and Gradually Boosting Performance on Resource-Constrained Environments
• Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models
• Light Differentiable Logic Gate Networks
• Prophecy: Inferring Formal Properties from Neuron Activations
• A Data-driven Typology of Vision Models from Integrated Representational Metrics
• LANCE: Low Rank Activation Compression for Efficient On-Device Continual Learning
• Temporal vs. Spatial: Comparing DINOv3 and V-JEPA2 Feature Representations for Video Action Analysis
• AI for Sustainable Future Foods
• Mammo-CLIP Dissect: A Framework for Analysing Mammography Concepts in Vision-Language Models
• Deep Adversarially-Enhanced k-Nearest Neighbors
• Short-term Load Forecasting with Deep Residual Networks
• Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017)
• DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
• Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
• Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
• The Taboo Trap: Behavioural Detection of Adversarial Samples
• Explanations can be manipulated and geometry is to blame
• MeshCNN
• ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks
• Data Augmentation for Skin Lesion using Self-Attention based Progressive\n Generative Adversarial Network
• Audio-Visual Transformer Based Crowd Counting
• Preparation Meets Opportunity: Enhancing Data Preprocessing for ML Training With Seneca
• On the basis of brain: neural-network-inspired changes in general-purpose chips
• Supervised Contrastive Learning
• Unleashing the Potential of the Semantic Latent Space in Diffusion Models for Image Dehazing
• Embodied AI: From LLMs to World Models
• GridMask Data Augmentation
• Impact of Loss Weight and Model Complexity on Physics-Informed Neural Networks for Computational Fluid Dynamics
• Sobolev acceleration for neural networks
• Mamba Modulation: On the Length Generalization of Mamba
• Adaptive von Mises-Fisher Likelihood Loss for Supervised Deep Time Series Hashing
• PAC-Bayes Analysis of Sentence Representation
• Learning to see across Domains and Modalities
• Thickened 2D Networks for Efficient 3D Medical Image Segmentation
• Not Only Look But Observe: Variational Observation Model of Scene-Level 3D Multi-Object Understanding for Probabilistic SLAM
• Deep Control - a simple automatic gain control for memory efficient and\n high performance training of deep convolutional neural networks
• Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference
• AutoGrow: Automatic Layer Growing in Deep Convolutional Networks
• Seesaw-Net: Convolution Neural Network With Uneven Group Convolution
• Structure-Aware Face Clustering on a Large-Scale Graph with \bf10⁷ Nodes
• Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
• Multi-task Learning by Leveraging the Semantic Information
• Understanding Submodular Information Measure Based Objectives for Representation Learning: A Variance and Separation Perspective
• Deep(er) Learning
• MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens
• Hybrid Composition with IdleBlock: More Efficient Networks for Image Recognition
• Temporal Poisoning: Clean-Label Backdoors via Event Redistribution in SNNs
• Deep learning for brake squeal: vibration detection, characterization and prediction
• Multi Layer Neural Networks as Replacement for Pooling Operations
• Lets keep it simple, Using simple architectures to outperform deeper and\n more complex architectures
• Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation
• Large-Scale Long-Tailed Recognition in an Open World
• Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning
• Artificial Intelligence Empowered New Materials: Discovery, Synthesis, Prediction to Validation
• Does the brain's ventral visual pathway compute object shape?
• Application of <scp>MobileNet</scp> and Xception neural networks to identify <scp> <i>Sillago sihama</i> </scp> populations in Vietnam's coastal waters based on otolith morphology
• Deep learning in plant phenotyping: the first ten years
• Quantitative Evaluations on Saliency Methods: An Experimental Study
• Deep learning‐based association analysis of root image data and cucumber yield
• Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition
• Feature refinement: An expression-specific feature learning and fusion method for micro-expression recognition
• Ellipse Regression with Predicted Uncertainties for Accurate Multi-View 3D Object Estimation
• DAIL: Dataset-Aware and Invariant Learning for Face Recognition
• When AI Meets Science: Research Diversity, Interdisciplinarity, Visibility, and Retractions across Disciplines in a Global Surge
• T-BFA: Targeted Bit-Flip Adversarial Weight Attack
• Multi-path Neural Networks for On-device Multi-domain Visual Classification
• Channel Tiling for Improved Performance and Accuracy of Optical Neural Network Accelerators
• Dynamic DNN Decomposition for Lossless Synergistic Inference
• Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations
• Dream-Cubed: Controllable Generative Modeling in Minecraft by Training on Billions of Cubes
• Semantic Understanding of Scenes Through the ADE20K Dataset
• PotentialNet for Molecular Property Prediction
• CLIP-Adapter: Better Vision-Language Models with Feature Adapters
• Selecting Data Augmentation for Simulating Interventions
• Gesture Recognition for Initiating Human-to-Robot Handovers
• Composition-Aware Image Aesthetics Assessment
• Unsupervised Intuitive Physics from Past Experiences
• Fuzzy Semantic Segmentation of Breast Ultrasound Image with Breast Anatomy Constraints
• Medical Image Segmentation Using a U-Net type of Architecture
• Thanks for Nothing: Predicting Zero-Valued Activations with Lightweight Convolutional Neural Networks
• A Deep Learning Framework for Classification of in vitro Multi-Electrode Array Recordings
• Inductive Bias of Gradient Descent based Adversarial Training on Separable Data
• Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays
• Compact deep neural network models of the visual cortex
• Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition
• SEALing Neural Network Models in Secure Deep Learning Accelerators
• Quantum Energy Regression using Scattering Transforms
• Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution
• Dense Adaptive Cascade Forest: A Self Adaptive Deep Ensemble for Classification Problems
• Gotta Adapt 'Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild
• k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks
• Application of Machine Learning for Aboveground Biomass Modeling in Tropical and Temperate Forests from Airborne Hyperspectral Imagery
• Use What You Know: Causal Foundation Models with Partial Graphs
• The steep cost of capture
• Monitoring urban construction and quarry blasts with low-cost seismic sensors and deep learning tools in the city of Oslo, Norway
• Identifying controlling factors of delta morphology using a convolutional autoencoder
• The Artificial Intelligence Cognitive Examination: A Survey on the Evolution of Multimodal Evaluation From Recognition to Reasoning
• EPick: Multi-Class Attention-based U-shaped Neural Network for Earthquake Detection and Seismic Phase Picking
• A Computer-Aided Diagnosis System for Breast Pathology: A Deep Learning Approach with Model Interpretability from Pathological Perspective
• A Performance Comparison of Loss Functions for Deep Face Recognition
• A highly selective response to food in human visual cortex revealed by hypothesis-free voxel decomposition
• Feature Space Augmentation for Long-Tailed Data
• On the Generalization Error Bounds of Neural Networks under Diversity-Inducing Mutual Angular Regularization
• Wireless for Machine Learning
• Auto-Encoding Twin-Bottleneck Hashing
• End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds
• A Geometric Approach to Online Streaming Feature Selection
• Deep Affinity Net: Instance Segmentation via Affinity
• Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognition
• Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning
• GRIPHIN: grids of pharmacophore interaction fields for affinity prediction
• The Brain Abstracted
• Edge-Enhanced Vision Transformer Framework for Accurate AI-Generated Image Detection
• Overcoming Data Sparsity in Group Recommendation
• Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification
• Not All Ops Are Created Equal!
• Handcrafted Backdoors in Deep Neural Networks
• A Survey of Autonomous Driving: <i>Common Practices and Emerging Technologies</i>
• What Do Single-view 3D Reconstruction Networks Learn?
• AutoFlow: Learning a Better Training Set for Optical Flow
• Algebraic Approach to Ridge-Regularized Mean Squared Error Minimization in Minimal ReLU Neural Network
• Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning
• Merchant Category Identification Using Credit Card Transactions
• Shape and Symmetry Induction for 3D Objects
• Detection of Furigana Text in Images
• Game-Theoretic Multiagent Reinforcement Learning
• Can We Faithfully Represent Masked States to Compute Shapley Values on a DNN?
• Robotic grasp detection using a novel two-stage approach
• TRACE: Early Detection of Chronic Kidney Disease Onset with Transformer-Enhanced Feature Embedding
• LoCo: Local Contrastive Representation Learning
• Biologically-inspired Salience Affected Artificial Neural Network (SANN)
• Video Anomaly Detection by Estimating Likelihood of Representations
• A Sheaf and Topology Approach to Generating Local Branch Numbers in Digital Images
• Robustness and Transferability of Universal Attacks on Compressed Models
• Seeing eye-to-eye? A comparison of object recognition performance in\n humans and deep convolutional neural networks under image manipulation
• Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images
• Why Convolutional Networks Learn Oriented Bandpass Filters: Theory and Empirical Support
• DSRNA: Differentiable Search of Robust Neural Architectures
• ParaNet: Deep Regular Representation for 3D Point Clouds
• KVL-BERT: Knowledge Enhanced Visual-and-Linguistic BERT for Visual Commonsense Reasoning
• Meticulous Object Segmentation
• Quantum computing tools for fast detection of gravitational waves in the context of LISA space mission
• Sketch-Specific Data Augmentation for Freehand Sketch Recognition
• Measurement-driven Security Analysis of Imperceptible Impersonation Attacks
• The Sloop System for Individual Animal Identification with Deep Learning
• Assessing the Alignment of Popular CNNs to the Brain for Valence Appraisal
• ROPA: Synthetic Robot Pose Generation for RGB-D Bimanual Data Augmentation
• Emergent symbolic language based deep medical image classification
• Pure Vision Language Action (VLA) Models: A Comprehensive Survey
• Visual Recognition Using Directional Distribution Distance
• ViG-LRGC: Vision Graph Neural Networks with Learnable Reparameterized Graph Construction
• Improving Outdoor Multi-cell Fingerprinting-based Positioning via Mobile Data Augmentation
• Hardness-Aware Deep Metric Learning
• Online and Offline Handwritten Chinese Character Recognition: A Comprehensive Study and New Benchmark
• Freehand Sketch Recognition Using Deep Features
• A Tutorial on Quantum Convolutional Neural Networks (QCNN)
• Uncertainty-aware Short-term Motion Prediction of Traffic Actors for\n Autonomous Driving
• LEAF-Mamba: Local Emphatic and Adaptive Fusion State Space Model for RGB-D Salient Object Detection
• Density-embedding layers: a general framework for adaptive receptive fields
• A Scalable Lift-and-Project Differentiable Approach For the Maximum Cut Problem
• OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC
• Machine learning approach to single-shot multiparameter estimation for the non-linear Schrödinger equation
• Automated Tracking of Primate Behavior
• Bounded PCTL Model Checking of Large Language Model Outputs
• Recognition Of Surface Defects On Steel Sheet Using Transfer Learning
• Detecting Deep Neural Network Defects with Data Flow Analysis
• Self-attention based BiLSTM-CNN classifier for the prediction of ischemic and non-ischemic cardiomyopathy
• Effective and efficient ROI-wise visual encoding using an end-to-end CNN regression model and selective optimization
• Towards Understanding and Modeling Empathy for Use in Motivational Design Thinking
• A Deep Ordinal Distortion Estimation Approach for Distortion Rectification
• SSFN -- Self Size-estimating Feed-forward Network with Low Complexity, Limited Need for Human Intervention, and Consistent Behaviour across Trials
• Six Sigma For Neural Networks: Taguchi-based optimization
• Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets
• Effectiveness of Data Augmentation in Cellular-based Localization Using Deep Learning
• DINOv3-Diffusion Policy: Self-Supervised Large Visual Model for Visuomotor Diffusion Policy Learning
• From Benchmarks to Reality: Advancing Visual Anomaly Detection by the VAND 3.0 Challenge
• Modeling Human Motion with Quaternion-Based Neural Networks
• The evolution of neural network-based chart patterns
• Neural network models and deep learning
• FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review
• Trustworthy Convolutional Neural Networks: A Gradient Penalized-based Approach
• A PMU-Based Machine Learning Application for Fast Detection of Forced Oscillations from Wind Farms
• Automatic Intermodal Loading Unit Identification using Computer Vision: A Scoping Review
• nDNA -- the Semantic Helix of Artificial Cognition
• SynergyNet: Fusing Generative Priors and State-Space Models for Facial Beauty Prediction
• SnipSnap: A Joint Compression Format and Dataflow Co-Optimization Framework for Efficient Sparse LLM Accelerator Design
• From handcrafted to deep local features
• Deep Clustering for Unsupervised Learning of Visual Features
• Guidelines and Benchmarks for Deployment of Deep Learning Models on\n Smartphones as Real-Time Apps
• A transfer learning method with deep residual network for pediatric pneumonia diagnosis
• Neural Network Based Framework for Passive Intermodulation Cancellation in MIMO Systems
• Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search
• A multiscale neural network based on hierarchical nested bases
• SOLAR: Switchable Output Layer for Accuracy and Robustness in Once-for-All Training
• Towards a Transparent and Interpretable AI Model for Medical Image Classifications
• Checking extracted rules in Neural Networks
• Randomized Smoothing Meets Vision-Language Models
• Ensemble Distillation for Robust Model Fusion in Federated Learning
• Deep learning algorithms for detection of diabetic retinopathy in retinal fundus photographs: A systematic review and meta-analysis
• Skeletal bone age prediction based on a deep residual network with spatial transformer
• A neural network approach to segment brain blood vessels in digital subtraction angiography
• ChartMaster: Advancing Chart-to-Code Generation with Real-World Charts and Chart Similarity Reinforcement Learning
• A vision transformer based approach for analysis of plasmodium vivax life cycle for malaria prediction using thin blood smear microscopic images
• A deep sift convolutional neural networks for total brain volume estimation from 3D ultrasound images
• Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications
• Region-Aware Deformable Convolutions
• Recent Advancements in Microscopy Image Enhancement using Deep Learning: A Survey
• Effect of Initial Configuration of Weights on Training and Function of Artificial Neural Networks
• Dissecting the Graphcore IPU Architecture via Microbenchmarking
• RGB-Only Supervised Camera Parameter Optimization in Dynamic Scenes
• Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey
• Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling
• Crafting GBD-Net for Object Detection
• Structure-Preserving Margin Distribution Learning for High-Order Tensor Data with Low-Rank Decomposition
• Exploring Self-attention for Image Recognition
• Task-Aware Monocular Depth Estimation for 3D Object Detection
• White-box machine learning for uncovering physically interpretable dimensionless governing equations for granular materials
• Adaptable image quality assessment using meta-reinforcement learning of task amenability
• Domain Generalization via Multidomain Discriminant Analysis
• Pointing Novel Objects in Image Captioning
• Survey on semantic segmentation using deep learning techniques
• Deep Learning For Computer Vision Tasks: A review
• Open-World Class Discovery with Kernel Networks
• Dynamic Spectrum Matching with One-shot Learning
• Unsupervised Object-Level Representation Learning from Scene Images
• MARIC: Multi-Agent Reasoning for Image Classification
• Learning FRAME Models Using CNN Filters
• Incorporating Visual Cortical Lateral Connection Properties into CNN: Recurrent Activation and Excitatory-Inhibitory Separation
• Deep Predictive Coding Network for Object Recognition
• Probabilistic Neural Network with Complex Exponential Activation\n Functions in Image Recognition using Deep Learning Framework
• Techniques for visualizing LSTMs applied to electrocardiograms
• Can you hear me \now? Sensitive comparisons of human and\n machine perception
• DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs
• Towards Robust Defense against Customization via Protective Perturbation Resistant to Diffusion-based Purification
• Binary Classification of Light and Dark Time Traces of a Transition Edge Sensor Using Convolutional Neural Networks
• Embedding Label Structures for Fine-Grained Feature Representation
• Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation
• Rest2Visual: Predicting Visually Evoked fMRI from Resting-State Scans
• A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification
• TreeIRL: Safe Urban Driving with Tree Search and Inverse Reinforcement Learning
• Intelligent Vacuum Thermoforming Process
• RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition
• Robot-Assisted Feeding: Generalizing Skewering Strategies across Food Items on a Realistic Plate
• On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions
• Deep Learning for Design and Retrieval of Nano-photonic Structures
• Transfer Metric Learning: Algorithms, Applications and Outlooks
• Proof of Federated Learning: A Novel Energy-recycling Consensus Algorithm
• EByFTVeS: Efficient Byzantine Fault Tolerant-based Verifiable Secret-sharing in Distributed Privacy-preserving Machine Learning
• TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks
• Revisiting Fine-tuning for Few-shot Learning
• BATR-FST: Bi-Level Adaptive Token Refinement for Few-Shot Transformers
• Multi-level Wavelet Convolutional Neural Networks
• High-resolution rainfall-runoff modeling using graph neural network
• DARTS: Deceiving Autonomous Cars with Toxic Signs
• A Robust and Precise ConvNet for small non-coding RNA classification\n (RPC-snRC)
• A Data-Aware Fourier Neural Operator for Modeling Spatiotemporal Electromagnetic Fields
• Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System
• Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
• A Survey on Neural Architecture Search
• On the Decision Boundary of Deep Neural Networks
• A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model
• Spherical Convolutional Neural Networks: Stability to Perturbations in SO(3)
• Advancing chest X-ray diagnostics: A novel CycleGAN-based preprocessing approach for enhanced lung disease classification in ChestX-Ray14
• Proposal Learning for Semi-Supervised Object Detection
• A Random Matrix Perspective on Mixtures of Nonlinearities for Deep Learning
• Overlearning Reveals Sensitive Attributes
• Toward Filament Segmentation Using Deep Neural Networks
• Microsoft COCO Captions: Data Collection and Evaluation Server
• Future Frame Prediction for Anomaly Detection -- A New Baseline
• Tubelets: Unsupervised action proposals from spatiotemporal super-voxels
• Scene Labeling with Contextual Hierarchical Models
• VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text
• FusionMAE: large-scale pretrained model to optimize and simplify diagnostic and control of fusion plasma
• PhotoApp: Photorealistic Appearance Editing of Head Portraits
• Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
• Beyond Triplet Loss: Meta Prototypical N-tuple Loss for Person Re-identification
• RGP: Neural Network Pruning through Its Regular Graph Structure
• TFD-former: Time-frequency domain fusion decoders for effective and robust fault diagnosis under time-varying speeds
• SCA-PVNet: Self-and-cross attention based aggregation of point cloud and multi-view for 3D object retrieval
• Subject-independent Human Pose Image Construction with Commodity Wi-Fi
• MailLeak: Obfuscation-Robust Character Extraction Using Transfer Learning
• Relating Graph Neural Networks to Structural Causal Models
• Deep Learning in Memristive Nanowire Networks
• Univariate ReLU neural network and its application in nonlinear system identification
• Learning Two-Branch Neural Networks for Image-Text Matching Tasks
• Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples
• Classifier Crafting: Turn Your ConvNet into a Zero-Shot Learner!
• Learning Deep Representations of Fine-grained Visual Descriptions
• Addressing Failure Prediction by Learning Model Confidence
• Flows Over Periodic Hills of Parameterized Geometries: A Dataset for Data-Driven Turbulence Modeling From Direct Simulations
• Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
• MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers
• Causal-Symbolic Meta-Learning (CSML): Inducing Causal World Models for Few-Shot Generalization
• Synetgy
• Deep learning with asymmetric connections and Hebbian updates
• Sitatapatra: Blocking the Transfer of Adversarial Samples
• A survey on deep learning approaches for breast cancer diagnosis
• Data augmentation and image understanding
• Artificial Neural Networks for Neuroscientists: A Primer
• LEGO: Spatial Accelerator Generation and Optimization for Tensor Applications
• Normalization Techniques in Training DNNs: Methodology, Analysis and Application
• Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition
• Unrolling Graph-based Douglas-Rachford Algorithm for Image Interpolation with Informed Initialization
• A Multiplexed Network for End-to-End, Multilingual OCR
• SugarcaneShuffleNet: A Very Fast, Lightweight Convolutional Neural Network for Diagnosis of 15 Sugarcane Leaf Diseases
• Customizing Student Networks From Heterogeneous Teachers via Adaptive Knowledge Amalgamation
• Efficient Algorithms for Device Placement of DNN Graph Operators
• The Neural Network Approach to Inverse Problems in Differential Equations
• Evaluating State-of-the-Art Classification Models Against Bayes Optimality
• IS-Diff: Improving Diffusion-Based Inpainting with Better Initial Seed
• Determining the boundary of dynamical chaos in the generalized Chirikov map via machine learning
• HyperInverter: Improving StyleGAN Inversion via Hypernetwork
• Recognizing American Sign Language Manual Signs from RGB-D Videos
• Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks
• A Controllable 3D Deepfake Generation Framework with Gaussian Splatting
• Efficient Byzantine-Robust Privacy-Preserving Federated Learning via Dimension Compression
• DISA at ImageCLEF 2014 Revised: Search-based Image Annotation with DeCAF Features
• Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements
• Mitigate Parasitic Resistance in Resistive Crossbar-based Convolutional Neural Networks
• gen2Out: Detecting and Ranking Generalized Anomalies
• Enhancing Electromagnetic Calorimeter Signal Reconstruction with Machine Learning-Based Noise Discrimination
• AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks
• Straggler-resistant distributed matrix computation via coding theory
• InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining
• Neural networks in the search for fast radio bursts with RATAN-600
• Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
• Self-Attention Capsule Networks for Object Classification
• Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition
• An Advanced Convolutional Neural Network for Bearing Fault Diagnosis under Limited Data
• Compact Device Models for FinFET and Beyond
• Unlabeled Data Deployment for Classification of Diabetic Retinopathy Images Using Knowledge Transfer
• Weakly Supervised Vulnerability Localization via Multiple Instance Learning
• Sinogram super-resolution and denoising convolutional neural network (SRCN) for limited data photoacoustic tomography
• Review: deep learning on 3D point clouds
• Two-Phase Object-Based Deep Learning for Multi-temporal SAR Image Change Detection
• A survey on Deep Learning based bearing fault diagnosis
• Neural Autoregressive Distribution Estimation
• Learnable Gabor modulated complex-valued networks for orientation robustness
• Deep Learning for Generic Object Detection: A Survey
• Rethinking Channel Dimensions for Efficient Model Design
• Characterizing the Efficiency of Distributed Training: A Power, Performance, and Thermal Perspective
• Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities
• A Critical Review of Recurrent Neural Networks for Sequence Learning
• Identification of Crystal Symmetry from Noisy Diffraction Patterns by A Shape Analysis and Deep Learning
• A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning
• A Capsule-unified Framework of Deep Neural Networks for Graphical Programming
• Knowledge Transfer via Dense Cross-Layer Mutual-Distillation
• Deep convolutional neural networks in the face of caricature
• Exploring Weight Symmetry in Deep Neural Networks
• InverSynth: Deep Estimation of Synthesizer Parameter Configurations from\n Audio Signals
• Contrastive Learning with Stronger Augmentations
• Dense RepPoints: Representing Visual Objects with Dense Point Sets
• Identifying Pediatric Vascular Anomalies With Deep Learning
• Parameterized Knowledge Transfer for Personalized Federated Learning
• STFCN: Spatio-Temporal FCN for Semantic Video Segmentation
• NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability
• Expressive Power of Deep Networks on Manifolds: Simultaneous Approximation
• Person Re-identification: Past, Present and Future
• Image Deformation Meta-Networks for One-Shot Learning
• Objectness Similarity: Capturing Object-Level Fidelity in 3D Scene Evaluation
• Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection
• Automatic Cross-Replica Sharding of Weight Update in Data-Parallel Training
• MSDANet: A Multiscale Dual-Channel Spatial Attention Network with Depthwise Separable Convolution for Hyperspectral Image Classification
• Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning
• MultiGrain: a unified image embedding for classes and instances
• Diffusion-Based Action Recognition Generalizes to Untrained Domains
• Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review
• Renovating Parsing R-CNN for Accurate Multiple Human Parsing
• Compressing CNN models for resource-constrained systems by channel and layer pruning
• Modulating human brain responses via optimal natural image selection and synthetic image generation
• CNN-ViT Hybrid for Pneumonia Detection: Theory and Empiric on Limited Data without Pretraining
• Network Pruning via Transformable Architecture Search
• Deep Learning for Free-Hand Sketch: A Survey
• Line Segment Detection Using Transformers without Edges
• Multispectral CT Denoising via Simulation-Trained Deep Learning: Experimental Results at the ESRF BM18
• Review of Video Predictive Understanding: Early Action Recognition and Future Action Prediction
• Actor-Centric Relation Network
• EAST: An Efficient and Accurate Scene Text Detector
• Trellis Networks for Sequence Modeling
• Distilling the Knowledge in a Neural Network
• Boosted Training of Lightweight Early Exits for Optimizing CNN Image Classification Inference
• Dual-Thresholding Heatmaps to Cluster Proposals for Weakly Supervised Object Detection
• Label Smoothing++: Enhanced Label Regularization for Training Neural Networks
• RISC-NN: Use RISC, NOT CISC as Neural Network Hardware Infrastructure
• Rollout-LaSDI: Enhancing the long-term accuracy of Latent Space Dynamics
• Localized PCA-Net Neural Operators for Scalable Solution Reconstruction of Elliptic PDEs
• Impression Space from Deep Template Network
• Residual Dense Network for Image Restoration
• A Practical Deep Learning-Based Acoustic Side Channel Attack on Keyboards
• FusionLane: Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural Networks
• PBRnet: Pyramidal Bounding Box Refinement to Improve Object Localization Accuracy
• Efficient resource management in UAVs for Visual Assistance
• Dataset Distillation
• Language Self-Play For Data-Free Training
• Three Pillars improving Vision Foundation Model Distillation for Lidar
• Spectral and Rhythm Feature Performance Evaluation for Category and Class Level Audio Classification with Deep Convolutional Neural Networks
• GLEAM: Learning to Match and Explain in Cross-View Geo-Localization
• Temporal Image Forensics: A Review and Critical Evaluation
• Enhanced Memory Network: The novel network structure for Symbolic Music Generation
• Revisiting the Calibration of Modern Neural Networks
• Stochastic Sign Descent Methods: New Algorithms and Better Theory
• Inferring brain-computational mechanisms with models of activity\n measurements
• Evaluating the Impact of Adversarial Attacks on Traffic Sign Classification using the LISA Dataset
• Data-driven discovery of dynamical models in biology
• Video Anomaly Detection and Localization via Gaussian Mixture Fully Convolutional Variational Autoencoder
• An Analysis of Scale Invariance in Object Detection - SNIP
• Expert-Guided Explainable Few-Shot Learning for Medical Image Diagnosis
• Foldover Features for Dynamic Object Behavior Description in Microscopic Videos
• Deep learning visual analysis in laparoscopic surgery: a systematic review and diagnostic test accuracy meta-analysis
• Comparison Network for One-Shot Conditional Object Detection
• Machine Learning: Algorithms, Real-World Applications and Research Directions
• Unifying Remote Sensing Image Retrieval and Classification with Robust Fine-tuning
• Adaptive, Distribution-Free Prediction Intervals for Deep Networks
• Laguerre-Gauss Preprocessing: Line Profiles as Image Features for Aerial\n Images Classification
• Image Enhanced Rotation Prediction for Self-Supervised Learning
• Dimensionally Reduced Open-World Clustering: DROWCULA
• Lookup multivariate Kolmogorov-Arnold Networks
• AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
• Albumentations: Fast and Flexible Image Augmentations
• Data-Efficient Time-Dependent PDE Surrogates: Graph Neural Simulators vs. Neural Operators
• RPC: A Large-Scale Retail Product Checkout Dataset
• Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks
• Fooling Computer Vision into Inferring the Wrong Body Mass Index
• Micro-Expression Recognition via Fine-Grained Dynamic Perception
• Agglomerative Attention
• Three-Dimensional Mesh Steganography and Steganalysis: A Review
• A brain-inspired paradigm for scalable quantum vision
• Unity Style Transfer for Person Re-Identification
• DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection
• DeepPoison: Feature Transfer Based Stealthy Poisoning Attack
• Explainable AI: A Review of Machine Learning Interpretability Methods
• Dual-Mode Deep Anomaly Detection for Medical Manufacturing: Structural Similarity and Feature Distance
• High Utilization Energy-Aware Real-Time Inference Deep Convolutional Neural Network Accelerator
• Simulation Priors for Data-Efficient Deep Learning
• Rethinking Supervised Pre-training for Better Downstream Transferring
• Prior Distribution and Model Confidence
• Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training
• Systematic Review and Meta-analysis of AI-driven MRI Motion Artifact Detection and Correction
• Lite-HRNet: A Lightweight High-Resolution Network
• Space-time Mixing Attention for Video Transformer
• TemporalFlowViz: Parameter-Aware Visual Analytics for Interpreting Scramjet Combustion Evolution
• Combating the Elsagate phenomenon: Deep learning architectures for disturbing cartoons
• Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters
• Graph Unlearning: Efficient Node Removal in Graph Neural Networks
• Advanced Brain Tumor Segmentation Using EMCAD: Efficient Multi-scale Convolutional Attention Decoding
• Scale-interaction transformer: a hybrid cnn-transformer model for facial beauty prediction
• Deep Learning Approaches for Image Retrieval and Pattern Spotting in\n Ancient Documents
• Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks
• Convolutional Dictionary Learning in Hierarchical Networks
• Dynamic Sensitivity Filter Pruning using Multi-Agent Reinforcement Learning For DCNN's
• On the Normalization of Confusion Matrices: Methods and Geometric Interpretations
• Bayesian Loss for Crowd Count Estimation with Point Supervision
• SpecNet: Spectral Domain Convolutional Neural Network
• Universality of Gradient Descent Neural Network Training
• Video Analytics with Zero-streaming Cameras
• Towards Open World Detection: A Survey
• Empirical Studies on the Properties of Linear Regions in Deep Neural Networks
• VCMamba: Bridging Convolutions with Multi-Directional Mamba for Efficient Visual Representation
• Measuring the Measures: Discriminative Capacity of Representational Similarity Metrics Across Model Families
• Delta Activations: A Representation for Finetuned Large Language Models
• Hyper Diffusion Avatars: Dynamic Human Avatar Generation using Network Weight Space Diffusion
• Light Field Reconstruction via Deep Adaptive Fusion of Hybrid Lenses
• Differential Morphological Profile Neural Networks for Semantic Segmentation
• Transformer-based Multi-Aspect Modeling for Multi-Aspect Multi-Sentiment Analysis
• A Survey on 3D Skeleton-Based Action Recognition Using Learning Method
• Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images
• Improving the Accuracy and Hardware Efficiency of Neural Networks Using Approximate Multipliers
• Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence
• SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
• Deep Gamblers: Learning to Abstain with Portfolio Theory
• Understanding Architectures Learnt by Cell-based Neural Architecture Search
• 1D convolutional neural networks and applications: A survey
• From Predictions to Explanations: Explainable AI for Autism Diagnosis and Identification of Critical Brain Regions
• Spatiotemporal Pyramid Network for Video Action Recognition
• ResiliNet: Failure-Resilient Inference in Distributed Neural Networks
• How Important is the Train-Validation Split in Meta-Learning?
• Watermarking Graph Neural Networks based on Backdoor Attacks
• Semantic Segmentation from Limited Training Data
• Moment Matching for Multi-Source Domain Adaptation
• Robust Training of Social Media Image Classification Models for Rapid Disaster Response
• Learning to See before Learning to Act: Visual Pre-training for Manipulation
• Sparse Autoencoder Neural Operators: Model Recovery in Function Spaces
• LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization
• FastCaps: A Design Methodology for Accelerating Capsule Network on Field Programmable Gate Arrays
• Isolated Bangla Handwritten Character Classification using Transfer Learning
• Minimizing Perceived Image Quality Loss Through Adversarial Attack\n Scoping
• CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows
• Understanding deep learning requires rethinking generalization
• End-to-end acoustic modeling using convolutional neural networks for HMM-based automatic speech recognition
• Directional Bias Amplification
• Long-Term Vehicle Localization by Recursive Knowledge Distillation
• Network Implosion: Effective Model Compression for ResNets via Static Layer Pruning and Retraining
• Human De-occlusion: Invisible Perception and Recovery for Humans
• MIDI-Sandwich2: RNN-based Hierarchical Multi-modal Fusion Generation VAE networks for multi-track symbolic music generation
• Residual Squeeze VGG16
• Stealth by Conformity: Evading Robust Aggregation through Adaptive Poisoning
• Multi-Scale Deep Learning for Colon Histopathology: A Hybrid Graph-Transformer Approach
• A Polynomial-Based Approach for Architectural Design and Learning with\n Deep Neural Networks
• Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training
• A Convolutional Hierarchical Deep-learning Neural Network (C-HiDeNN) Framework for Non-linear Finite Element Analysis
• Vision encoders should be image size agnostic and task driven
• MixKD: Towards Efficient Distillation of Large-scale Language Models
• Vision-based deep execution monitoring
• MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices
• Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection
• The gap between theory and practice in function approximation with deep neural networks
• On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
• Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions
• FAWA: Fast Adversarial Watermark Attack on Optical Character Recognition (OCR) Systems
• Pruning Convolutional Neural Networks with Self-Supervision
• Robots of the Lost Arc: Self-Supervised Learning to Dynamically Manipulate Fixed-Endpoint Cables
• Robust Small Methane Plume Segmentation in Satellite Imagery
• One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification
• LaSOT: A High-quality Large-scale Single Object Tracking Benchmark
• TensorLib: A Spatial Accelerator Generation Framework for Tensor Algebra
• HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens
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• ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
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• Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation
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• Characterizing Types of Convolution in Deep Convolutional Recurrent Neural Networks for Robust Speech Emotion Recognition
• Generalized Zero-Shot Domain Adaptation via Coupled Conditional Variational Autoencoders
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• URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection
• Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos
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• Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
• Diversity inducing Information Bottleneck in Model Ensembles
• A Runtime-Based Computational Performance Predictor for Deep Neural Network Training
• Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images
• MemeSequencer: Sparse Matching for Embedding Image Macros
• Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent
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• TransMatch: A Transfer-Learning Framework for Defect Detection in Laser Powder Bed Fusion Additive Manufacturing
• SoK: Understanding the Fundamentals and Implications of Sensor Out-of-band Vulnerabilities
• Mamba-CNN: A Hybrid Architecture for Efficient and Accurate Facial Beauty Prediction
• Lightweight and Fast Real-time Image Enhancement via Decomposition of the Spatial-aware Lookup Tables
• Towards More Diverse and Challenging Pre-training for Point Cloud Learning: Self-Supervised Cross Reconstruction with Decoupled Views
• Contrastive Model Inversion for Data-Free Knowledge Distillation
• MSE Loss with Outlying Label for Imbalanced Classification
• Learning Connectivity of Neural Networks from a Topological Perspective
• Towards Deep Learning Assisted Autonomous UAVs for Manipulation Tasks in GPS-Denied Environments
• Plant Disease Detection and Classification by Deep Learning—A Review
• Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification
• Proximal Backpropagation
• SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation
• Performance evaluation of an integrated photonic convolutional neural network based on delay buffering and wavelength division multiplexing
• The Limitations of Deep Learning in Adversarial Settings
• Move Evaluation in Go Using Deep Convolutional Neural Networks
• Probabilistic Permutation Synchronization using the Riemannian Structure\n of the Birkhoff Polytope
• OnlineAugment: Online Data Augmentation with Less Domain Knowledge
• Assessing the (Un)Trustworthiness of Saliency Maps for Localizing\n Abnormalities in Medical Imaging
• Routing Towards Discriminative Power of Class Capsules
• From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation
• COVID-19 personal protective equipment detection using real-time deep learning methods
• Modeling the Nonsmoothness of Modern Neural Networks
• Lung cancer identification: a review on detection and classification
• Compact Deep Aggregation for Set Retrieval
• Towards Accurate and Compact Architectures via Neural Architecture Transformer
• Understanding and Enhancing the Use of Context for Machine Translation
• Learning by training: emergent return-point memory from cyclically tuning disordered sphere packings
• Using Distance Estimation and Deep Learning to Simplify Calibration in\n Food Calorie Measurement
• Rethinking FUN: Frequency-Domain Utilization Networks
• Deep Learning on Image Denoising: An overview
• A differential neural network learns stochastic differential equations and the Black-Scholes equation for pricing multi-asset options
• Regularization via Mass Transportation
• Partial success in closing the gap between human and machine vision
• Application of discrete Ricci curvature in pruning randomly wired neural networks: A case study with chest x-ray classification of COVID-19
• C-DiffDet+: Fusing Global Scene Context with Generative Denoising for High-Fidelity Car Damage Detection
• Incremental Learning with Maximum Entropy Regularization: Rethinking\n Forgetting and Intransigence
• Unsupervised Domain Adaptation Learning Algorithm for RGB-D Staircase Recognition
• Dropout drops double descent
• CNN with large memory layers
• Generative Latent Space Dynamics of Electron Density
• Cross-Attention Multimodal Fusion for Breast Cancer Diagnosis: Integrating Mammography and Clinical Data with Explainability
• Understanding the Behaviour of Contrastive Loss
• Optimization Variance: Exploring Generalization Properties of DNNs
• Artificial Intelligence in Drug Discovery: Applications and Techniques
• AI Compute Architecture and Evolution Trends
• Representation Learning with Adaptive Superpixel Coding
• CuratorNet: Visually-aware Recommendation of Art Images
• Accelerated Training for Massive Classification via Dynamic Class Selection
• DeepOPF: Deep Neural Network for DC Optimal Power Flow
• OmniArt: Multi-task Deep Learning for Artistic Data Analysis
• Accelerating Federated Learning via Momentum Gradient Descent
• Convolutional Neural Fabrics
• Playing Atari with Deep Reinforcement Learning
• Survey of spiking in the mouse visual system reveals functional hierarchy
• EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
• Cyclone intensity estimate with context-aware cyclegan
• Deep Anomaly Detection by Residual Adaptation
• Estimating Model Uncertainty of Neural Networks in Sparse Information\n Form
• Collective Learning by Ensembles of Altruistic Diversifying Neural Networks
• Efficient Integer-Arithmetic-Only Convolutional Neural Networks
• Learning compact generalizable neural representations supporting perceptual grouping
• IA-RED²: Interpretability-Aware Redundancy Reduction for Vision Transformers
• GODS: Generalized One-class Discriminative Subspaces for Anomaly Detection
• Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
• Microscopic and collective signatures of feature learning in neural networks
• E-ConvNeXt: A Lightweight and Efficient ConvNeXt Variant with Cross-Stage Partial Connections
• Data-Free Adversarial Distillation
• Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science
• D3PINNs: A Novel Physics-Informed Neural Network Framework for Staged Solving of Time-Dependent Partial Differential Equations
• Network Representation Learning: From Traditional Feature Learning to Deep Learning
• Developing a Multi-Modal Machine Learning Model For Predicting Performance of Automotive Hood Frames
• Understanding Incremental Learning with Closed-form Solution to Gradient Flow on Overparamerterized Matrix Factorization
• 3D-Aided Data Augmentation for Robust Face Understanding
• A Chain Graph Interpretation of Real-World Neural Networks
• Character-Aware Neural Language Models
• Improving Adversarial Robustness via Guided Complement Entropy
• Recovery Guarantees for Compressible Signals with Adversarial Noise
• Computational Emotion Analysis From Images: Recent Advances and Future Directions
• Iterative Low-Rank Approximation for CNN Compression
• What makes instance discrimination good for transfer learning?
• A Spatial-Frequency Aware Multi-Scale Fusion Network for Real-Time Deepfake Detection
• Exploring Randomly Wired Neural Networks for Image Recognition
• Objective Value Change and Shape-Based Accelerated Optimization for the Neural Network Approximation
• Seam360GS: Seamless 360° Gaussian Splatting from Real-World Omnidirectional Images
• Eigenvalue distribution of the Neural Tangent Kernel in the quadratic scaling
• Improving Calibration for Long-Tailed Recognition
• Radioactive data: tracing through training
• Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting
• Measuring Dataset Granularity
• How Does Batch Normalization Help Optimization?
• Symplectic convolutional neural networks
• Improving Generalization in Deepfake Detection with Face Foundation Models and Metric Learning
• Task-Generalized Adaptive Cross-Domain Learning for Multimodal Image Fusion
• Causal Intervention for Weakly-Supervised Semantic Segmentation
• PRADA: Protecting against DNN Model Stealing Attacks
• Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
• Multiscale Deep Equilibrium Models
• Mini-Batch Robustness Verification of Deep Neural Networks
• The GINN framework: a stochastic QED correspondence for stability and chaos in deep neural networks
• DeepOPF: A Deep Neural Network Approach for Security-Constrained DC Optimal Power Flow
• WIDER FACE: A Face Detection Benchmark
• Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks
• Alljoined-1.6M: A Million-Trial EEG-Image Dataset for Evaluating Affordable Brain-Computer Interfaces
• Return of the Devil in the Details: Delving Deep into Convolutional Nets
• Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
• PanNuke Dataset Extension, Insights and Baselines
• Benchmarking Deep Reinforcement Learning for Continuous Control
• Bladder Cancer Diagnosis with Deep Learning: A Multi-Task Framework and Online Platform
• VQualA 2025 Challenge on Face Image Quality Assessment: Methods and Results
• Real-Time User-Guided Image Colorization with Learned Deep Priors
• Discretization-Aware Architecture Search
• PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration
• Systematic evaluation of convolution neural network advances on the Imagenet
• Robust and Efficient Quantum Reservoir Computing with Discrete Time Crystal
• Enhancing Adversarial Example Transferability with an Intermediate Level Attack
• AutoHOOT: Automatic High-Order Optimization for Tensors
• Use of Transfer Learning and Wavelet Transform for Breast Cancer Detection
• Ontology Based Global and Collective Motion Patterns for Event Classification in Basketball Videos
• Deep learning for the semi-classical limit of the Schrödinger equation
• Optimistic and Pessimistic Neural Networks for Scene and Object Recognition
• Attended End-to-end Architecture for Age Estimation from Facial Expression Videos
• ModelHub.AI: Dissemination Platform for Deep Learning Models
• Richer priors for infinitely wide multi-layer perceptrons
• Unpaired Image Translation via Adaptive Convolution-based Normalization
• Learning to Fuse Things and Stuff
• On the approximation of the solution of partial differential equations by artificial neural networks trained by a multilevel Levenberg-Marquardt method
• Frequency-adaptive tensor neural networks for high-dimensional multi-scale problems
• DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding
• Snap-Snap: Taking Two Images to Reconstruct 3D Human Gaussians in Milliseconds
• Study and development of a Computer-Aided Diagnosis system for classification of chest x-ray images using convolutional neural networks pre-trained for ImageNet and data augmentation
• Bias-based Universal Adversarial Patch Attack for Automatic Check-out
• Synthetic Adaptive Guided Embeddings (SAGE): A Novel Knowledge Distillation Method
• Real-time Human Detection Model for Edge Devices
• Convolutional Neural Network Pruning with Structural Redundancy Reduction
• Deep Learning for Taxol Exposure Analysis: A New Cell Image Dataset and Attention-Based Baseline Model
• On the Communication Latency of Wireless Decentralized Learning
• Minimizing Task-Oriented Age of Information for Remote Monitoring with Pre-Identification
• Improving OCR using internal document redundancy
• MoCHA-former: Moiré-Conditioned Hybrid Adaptive Transformer for Video Demoiréing
• Towards Precise End-to-end Weakly Supervised Object Detection Network
• Improved Mapping Between Illuminations and Sensors for RAW Images
• CP-mtML: Coupled Projection multi-task Metric Learning for Large Scale\n Face Retrieval
• Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
• Neo
• Discriminative Noise Robust Sparse Orthogonal Label Regression-based Domain Adaptation
• Normalized Cut Loss for Weakly-supervised CNN Segmentation
• Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes
• Lottery Jackpots Exist in Pre-trained Models
• Neural Image Beauty Predictor Based on Bradley-Terry Model
• Defeating Catastrophic Forgetting via Enhanced Orthogonal Weights Modification
• Busy-Quiet Video Disentangling for Video Classification
• MOPS-Net: A Matrix Optimization-driven Network forTask-Oriented 3D Point Cloud Downsampling
• Capsule GAN Using Capsule Network for Generator Architecture
• MixHop: Higher-Order Graph Convolutional Architectures via Sparsified\n Neighborhood Mixing
• SVM and ELM: Who Wins? Object Recognition with Deep Convolutional Features from ImageNet
• On the Evaluation Metric for Hashing
• How to Train Your MAML to Excel in Few-Shot Classification
• torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models
• Representative Forgery Mining for Fake Face Detection
• CHAIN: Concept-harmonized Hierarchical Inference Interpretation of Deep Convolutional Neural Networks
• Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection
• Open Set Domain Adaptation for Image and Action Recognition
• An Acoustic Segment Model Based Segment Unit Selection Approach to Acoustic Scene Classification with Partial Utterances
• A Survey on Video Anomaly Detection via Deep Learning: Human, Vehicle, and Environment
• Spherical U-Net on Cortical Surfaces: Methods and Applications
• One Shot vs. Iterative: Rethinking Pruning Strategies for Model Compression
• Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation
• FLAIR: Frequency- and Locality-Aware Implicit Neural Representations
• Evaluating Open-Source Vision Language Models for Facial Emotion Recognition against Traditional Deep Learning Models
• A Study of BFLOAT16 for Deep Learning Training
• Genuine multipartite entanglement verification with convolutional neural networks
• SpherePHD: Applying CNNs on a Spherical PolyHeDron Representation of 360\n degree Images
• Training with the Invisibles: Obfuscating Images to Share Safely for Learning Visual Recognition Models
• Deeply Exploit Depth Information for Object Detection
• Lightweight Convolutional Representations for On-Device Natural Language Processing
• Unsupervised Domain Adaptation for Semantic Segmentation via Low-level Edge Information Transfer
• NeuroView: Explainable Deep Network Decision Making
• Optimization problems for machine learning: A survey
• ONG: One-Shot NMF-based Gradient Masking for Efficient Model Sparsification
• Uncertainty Propagation in Deep Neural Network Using Active Subspace
• D2-Mamba: Dual-Scale Fusion and Dual-Path Scanning with SSMs for Shadow Removal
• Creative4U: MLLMs-based Advertising Creative Image Selector with Comparative Reasoning
• SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction
• Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination
• The Pitfall of Evaluating Performance on Emerging AI Accelerators
• RED-NET: A Recursive Encoder-Decoder Network for Edge Detection
• NESTA: Hamming Weight Compression-Based Neural Proc. Engine
• Contextual Local Explanation for Black Box Classifiers
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• Skin Cancer Classification: Hybrid CNN-Transformer Models with KAN-Based Fusion
• Efficient and Verifiable Privacy-Preserving Convolutional Computation for CNN Inference with Untrusted Clouds
• Attentive Deep Regression Networks for Real-Time Visual Face Tracking in Video Surveillance
• Seek and You Will Find: A New Optimized Framework for Efficient Detection of Pedestrian
• An ECC-based Fault Tolerance Approach for DNNs
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• Belief-Conditioned One-Step Diffusion: Real-Time Trajectory Planning with Just-Enough Sensing
• TriQDef: Disrupting Semantic and Gradient Alignment to Prevent Adversarial Patch Transferability in Quantized Neural Networks
• ViPTT-Net: Video pretraining of spatio-temporal model for tuberculosis type classification from chest CT scans
• HALO: Learning to Prune Neural Networks with Shrinkage
• Importance Filtered Cross-Domain Adaptation
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• Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm
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• DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
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• NeMo: A Neuron-Level Modularizing-While-Training Approach for Decomposing DNN Models
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• FedNS: Improving Federated Learning for collaborative image classification on mobile clients
• Master Thesis: Neural Sign Language Translation by Learning Tokenization
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• health effects of dielectric gases: preliminary report
• Understanding the Error in Evaluating Adversarial Robustness
• Mobile-Friendly Deep Learning for Plant Disease Detection: A Lightweight CNN Benchmark Across 101 Classes of 33 Crops
• Self-Paced Uncertainty Estimation for One-shot Person Re-Identification
• NASA: Neural Articulated Shape Approximation
• Dissecting Generalized Category Discovery: Multiplex Consensus under Self-Deconstruction
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• ModiPick: SLA-aware Accuracy Optimization For Mobile Deep Inference
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• CRISP: Contrastive Residual Injection and Semantic Prompting for Continual Video Instance Segmentation
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• Collegial Ensembles
• Transfer Learning for Melanoma Detection: Participation in ISIC 2017 Skin Lesion Classification Challenge
• Toward Lifelong Learning in Equilibrium Propagation: Sleep-like and Awake Rehearsal for Enhanced Stability
• Hashing as Tie-Aware Learning to Rank
• AI-Skin : Skin Disease Recognition based on Self-learning and Wide Data Collection through a Closed Loop Framework
• PAC-GAN: An Effective Pose Augmentation Scheme for Unsupervised Cross-View Person Re-identification
• Image selective encryption analysis using mutual information in CNN based embedding space
• Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested LSTM Models
• Continuous Perception for Classifying Shapes and Weights of Garmentsfor Robotic Vision Applications
• Automated Decision-based Adversarial Attacks
• Controlling Covariate Shift using Balanced Normalization of Weights
• Flexible Dataset Distillation: Learn Labels Instead of Images
• Implementation of Deep Neural Networks to Classify EEG Signals using Gramian Angular Summation Field for Epilepsy Diagnosis
• Sparse tree-based initialization for neural networks
• Reinforcement learning for batch bioprocess optimization
• Defending Against Image Corruptions Through Adversarial Augmentations
• Interpretable CNNs for Object Classification
• Regularized Adaptation for Stable and Efficient Continuous-Level\n Learning on Image Processing Networks
• An Intelligent Group Event Recommendation System in Social networks
• Understanding the Limitations of Variational Mutual Information Estimators
• CNN Acceleration by Low-rank Approximation with Quantized Factors
• Detecting Mislabeled and Corrupted Data via Pointwise Mutual Information
• Self-Supervised Representation Learning for Visual Anomaly Detection
• Active Learning for Breast Cancer Identification
• Cooperative Bi-path Metric for Few-shot Learning
• Lightweight Multi-Scale Feature Extraction with Fully Connected LMF Layer for Salient Object Detection
• Why Does Stochastic Gradient Descent Slow Down in Low-Precision Training?
• A Bayesian Data Augmentation Approach for Learning Deep Models
• Multi-scale Domain-adversarial Multiple-instance CNN for Cancer Subtype Classification with Unannotated Histopathological Images
• PU-Net: Point Cloud Upsampling Network
• Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization
• Learning to Generate 3D Shapes with Generative Cellular Automata
• Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks
• MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction
• Diffeomorphic Neural Operator Learning
• Confounder Identification-free Causal Visual Feature Learning
• Position: Ideas Should be the Center of Machine Learning Research
• Multimodal learning with next-token prediction for large multimodal models
• Deep Convolutional Decision Jungle for Image Classification
• Lung sounds classification using convolutional neural networks
• Ophthalmic diagnosis using deep learning with fundus images – A critical review
• Medical knowledge embedding based on recursive neural network for multi-disease diagnosis
• Enhancing Recognition and Categorization of Skin Lesions with Tailored Deep Convolutional Networks and Robust Data Augmentation Techniques
• Fast Calculation of Probabilistic Power Flow: A Model-based Deep Learning Approach
• Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep\n Neural Networks
• Reinforced Evolutionary Neural Architecture Search
• Alleviating Mode Collapse in GAN via Diversity Penalty Module
• Affective Image Content Analysis: Two Decades Review and New Perspectives
• Parallel Deep Neural Networks Have Zero Duality Gap
• Facial Information Analysis Technology for Gender and Age Estimation
• Being-ahead: Benchmarking and Exploring Accelerators for Hardware-Efficient AI Deployment
• Learning Representations of Satellite Images with Evaluations on Synoptic Weather Events
• Recurrent Deep Differentiable Logic Gate Networks
• Zero-Shot Learning by Convex Combination of Semantic Embeddings
• Synthetic Data Generation for Emotional Depth Faces: Optimizing Conditional DCGANs via Genetic Algorithms in the Latent Space and Stabilizing Training with Knowledge Distillation
• Multi-view Gaze Target Estimation
• Re-evaluating Evaluation
• Regularized Evolutionary Population-Based Training
• Optimising the Performance of Convolutional Neural Networks across Computing Systems using Transfer Learning
• A geometry-inspired decision-based attack
• Keep It Real: Challenges in Attacking Compression-Based Adversarial Purification
• Input Invex Neural Network
• A Study of Gender Classification Techniques Based on Iris Images: A Deep Survey and Analysis
• Real-time Detection of Practical Universal Adversarial Perturbations
• Multi-Labelled Value Networks for Computer Go
• Rotation Equivariant Arbitrary-scale Image Super-Resolution
• Digital Twin Channel-Aided CSI Prediction: An Environment-Based Subspace Extraction Approach for Achieving Low Overhead and High Robustness
• ULU: A Unified Activation Function
• Tesserae: Scalable Placement Policies for Deep Learning Workloads
• Self-Error Adjustment: Theory and Practice of Balancing Individual Performance and Diversity in Ensemble Learning
• Smaller Models, Better Generalization
• Toward Errorless Training ImageNet-1k
• Pulmonary embolism identification in computerized tomography pulmonary angiography scans with deep learning technologies in COVID-19 patients
• Robust Processing-In-Memory Neural Networks via Noise-Aware Normalization
• Metric Learning in an RKHS
• PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media
• DeePore: A deep learning workflow for rapid and comprehensive characterization of porous materials
• Adaptive Neuron-wise Discriminant Criterion and Adaptive Center Loss at Hidden Layer for Deep Convolutional Neural Network
• Automated ultrasound doppler angle estimation using deep learning
• Energy-Efficient Real-Time 4-Stage Sleep Classification at 10-Second Resolution: A Comprehensive Study
• Age-Diverse Deepfake Dataset: Bridging the Age Gap in Deepfake Detection
• Slice or the Whole Pie? Utility Control for AI Models
• Deep Cross Residual Learning for Multitask Visual Recognition
• Deep learning framework for crater detection and identification on the Moon and Mars
• Training Deep Neural Networks via Branch-and-Bound
• Automatic Detection of Coronavirus Disease (COVID-19) in X-ray and CT\n Images: A Machine Learning-Based Approach
• CADD: Context aware disease deviations via restoration of brain images using normative conditional diffusion models
• Relationship-Embedded Representation Learning for Grounding Referring Expressions
• Deep Reasoning with Multi-Scale Context for Salient Object Detection
• A Scalable Optimization Mechanism for Pairwise based Discrete Hashing
• Zero Shot Domain Adaptive Semantic Segmentation by Synthetic Data Generation and Progressive Adaptation
• The Power of Many: Synergistic Unification of Diverse Augmentations for Efficient Adversarial Robustness
• QuantNet: Learning to Quantize by Learning within Fully Differentiable Framework
• RoIFusion: 3D Object Detection from LiDAR and Vision
• Where and How to Enhance: Discovering Bit-Width Contribution for Mixed Precision Quantization
• TrackNet: A Deep Learning Network for Tracking High-speed and Tiny Objects in Sports Applications
• The Geometry of Cortical Computation: Manifold Disentanglement and Predictive Dynamics in VCNet
• Fully-Convolutional Siamese Networks for Object Tracking
• Domain Adaptation with Incomplete Target Domains
• Toward Practical Equilibrium Propagation: Brain-inspired Recurrent Neural Network with Feedback Regulation and Residual Connections
• Infrared Object Detection with Ultra Small ConvNets: Is ImageNet Pretraining Still Useful?
• Evaluation and Analysis of Deep Neural Transformers and Convolutional Neural Networks on Modern Remote Sensing Datasets
• Graph Classification Based on Skeleton and Component Features
• Towards Compact and Robust Deep Neural Networks
• FAIR-Pruner: Leveraging Tolerance of Difference for Flexible Automatic Layer-Wise Neural Network Pruning
• After the Party: Navigating the Mapping From Color to Ambient Lighting
• Deep Learning Face Representation by Joint Identification-Verification
• Fast Neural Network Adaptation via Parameter Remapping and Architecture Search
• Tackling Ill-posedness of Reversible Image Conversion with Well-posed Invertible Network
• Combining Ensembles and Data Augmentation can Harm your Calibration
• Defending Against Adversarial Attacks Using Random Forests
• GlaBoost: A multimodal Structured Framework for Glaucoma Risk Stratification
• Composite Quantization
• Improving Noise Efficiency in Privacy-preserving Dataset Distillation
• RaftMLP: How Much Can Be Done Without Attention and with Less Spatial Locality?
• Pulse Shape Discrimination Algorithms: Survey and Benchmark
• Discrete Rotation Equivariance for Point Cloud Recognition
• Set Pivot Learning: Redefining Generalized Segmentation with Vision Foundation Models
• Deep Built-Structure Counting in Satellite Imagery Using Attention Based\n Re-Weighting
• Reconstructing Trust Embeddings from Siamese Trust Scores: A Direct-Sum Approach with Fixed-Point Semantics
• Intensity augmentation for domain transfer of whole breast segmentation\n in MRI
• Increasing the Generalisation Capacity of Conditional VAEs
• Robust Visual Knowledge Transfer via EDA
• Translating Math Formula Images to LaTeX Sequences Using Deep Neural Networks with Sequence-level Training
• Partial observations and conservation laws: Grey-box modeling in\n biotechnology and optogenetics
• Yelp Food Identification via Image Feature Extraction and Classification
• Fusion Sampling Validation in Data Partitioning for Machine Learning
• A Simple and Effective Method for Uncertainty Quantification and OOD Detection
• Imbalanced Deep Learning by Minority Class Incremental Rectification
• Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning
• Learning Competitive and Discriminative Reconstructions for Anomaly Detection
• Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri--Rao Product
• Initialization Strategies of Spatio-Temporal Convolutional Neural\n Networks
• UIS-Mamba: Exploring Mamba for Underwater Instance Segmentation via Dynamic Tree Scan and Hidden State Weaken
• Variational Autoencoder-Based Black-Box Adversarial Attack on Collaborative DNN Inference
• Sinusoidal Approximation Theorem for Kolmogorov-Arnold Networks
• ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network
• EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes
• L-GTA: Latent Generative Modeling for Time Series Augmentation
• Beyond Linear Bottlenecks: Spline-Based Knowledge Distillation for Culturally Diverse Art Style Classification
• Learn molecular representations from large-scale unlabeled molecules for drug discovery
• Particle reconstruction of volumetric particle image velocimetry with strategy of machine learning
• Flow Contrastive Estimation of Energy-Based Models
• Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference
• Do We Need Fully Connected Output Layers in Convolutional Networks?
• Foundations and Models in Modern Computer Vision: Key Building Blocks in Landmark Architectures
• Initialization Using Perlin Noise for Training Networks with a Limited Amount of Data
• Your Spending Needs Attention: Modeling Financial Habits with Transformers
• Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform
• How deep should be the depth of convolutional neural networks: a backyard dog case study
• CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals
• SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning
• Describing Unseen Videos via Multi-Modal Cooperative Dialog Agents
• Graph Lineages and Skeletal Graph Products
• An Artificial Intelligence-Based System to Assess Nutrient Intake for Hospitalised Patients
• JQF: Optimal JPEG Quantization Table Fusion by Simulated Annealing on Texture Images and Predicting Textures
• Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods
• Tricks and Plug-ins for Gradient Boosting in Image Classification
• Multi-lane Detection Using Instance Segmentation and Attentive Voting
• Robust Collaborative Learning of Patch-level and Image-level Annotations for Diabetic Retinopathy Grading from Fundus Image
• Segment Anything for Video: A Comprehensive Review of Video Object Segmentation and Tracking from Past to Future
• Machine Learning for Detecting Data Exfiltration: A Review
• Explaining Natural Language Processing Classifiers with Occlusion and Language Modeling
• DACA-Net: A Degradation-Aware Conditional Diffusion Network for Underwater Image Enhancement
• Crowding in humans is unlike that in convolutional neural networks
• You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection
• Agentic Privacy-Preserving Machine Learning
• RCR-AF: Enhancing Model Generalization via Rademacher Complexity Reduction Activation Function
• Training a Binary Weight Object Detector by Knowledge Transfer for Autonomous Driving
• Knowledge-augmented Column Networks: Guiding Deep Learning with Advice
• StarNet: Targeted Computation for Object Detection in Point Clouds
• FDNAS: Improving Data Privacy and Model Diversity in AutoML
• Synthesizing Optimal Parallelism Placement and Reduction Strategies on Hierarchical Systems for Deep Learning
• TIR-Diffusion: Diffusion-based Thermal Infrared Image Denoising via Latent and Wavelet Domain Optimization
• Moiré Zero: An Efficient and High-Performance Neural Architecture for Moiré Removal
• Object Recognition Datasets and Challenges: A Review
• Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior. [europepmc]
• Computer-aided detection in chest radiography based on artificial intelligence: a survey. [europepmc]
• Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review. [europepmc]
• A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease. [europepmc]
• Artificial intelligence and machine learning in clinical development: a translational perspective. [europepmc]
• Key Topics in Molecular Docking for Drug Design. [europepmc]
• Artificial Intelligence in Lung Cancer Pathology Image Analysis. [europepmc]
• Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms. [europepmc]
• 3D Deep Learning on Medical Images: A Review. [europepmc]
• Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning. [europepmc]
• DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires. [europepmc]
• Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. [europepmc]
• The language of proteins: NLP, machine learning & protein sequences. [europepmc]
• Epileptic Seizures Detection Using Deep Learning Techniques: A Review. [europepmc]
• GNINA 1.0: molecular docking with deep learning. [europepmc]
• Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems. [europepmc]
• TransMed: Transformers Advance Multi-Modal Medical Image Classification. [europepmc]
• A review on deep learning in medical image analysis. [europepmc]
• Recent Advances in Electrochemical Biosensors: Applications, Challenges, and Future Scope. [europepmc]
• The Role of Artificial Intelligence in Early Cancer Diagnosis. [europepmc]
• Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE). [europepmc]
• A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images. [europepmc]
• Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review. [europepmc]
• Redefining Radiology: A Review of Artificial Intelligence Integration in Medical Imaging. [europepmc]
• How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications. [europepmc]

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