YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

2024/10/25 by Chien-Yao Wang, I-Hau Yeh, Hong-Yuan Mark Liao · 7 citations
Computer Science · Medicine · #Advanced Neural Network Applications #COVID-19 diagnosis using AI #Medical Image Segmentation Techniques

paper · doi:10.1007/978-3-031-72751-1_1

openalex publication_date 2024/10/25 · crossref created 2024/10/25 · crossref deposited 2024/10/25 · crossref issued 2024/10/26 · crossref published 2024/10/26 · crossref published-online 2024/10/26 · crossref published-print 2025/01/01 · openalex created_date 2025/10/10 · crossref indexed 2026/07/30 · openalex updated_date 2026/07/31

Citations

• Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
• CSPNet: A New Backbone that can Enhance Learning Capability of CNN
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
• PVT v2: Improved baselines with pyramid vision transformer
• Swin Transformer V2: Scaling Up Capacity and Resolution
• A ConvNet for the 2020s
• YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors
• DETRs Beat YOLOs on Real-time Object Detection

Cited by

• ADD-YOLO: a new model for object detection in aerial images
• Leveraging Big Multitemporal Multisource Satellite Data and Artificial Intelligence for the Detection of Complex and Invisible Features: The Case of Extensive Irrigation Mapping
• ImageBind Guided Progressive Transformation Network for Alignment-free RGBT Video Object Detection
• A Multi-Scale Perception-Enhanced Lightweight Network with Knowledge Distillation for Rice Leaf Disease Detection
• SS-YOLOv8: small-size object detection algorithm based on improved YOLOv8 for UAV imagery
• Scd-yolo: a novel object detection method for efficient road crack detection
• X-safe: an X-ray security detection method based on incremental Kernel aggregation, hierarchical co-optimization and task-aligned labeling