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José Oramas

  1. Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks
    2017/12/18 by José Oramas, Oramas, Jose, Kaili Wang +3 · 3 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Anomaly Detection Techniques and Applications #Cell Image Analysis Techniques #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  2. Bilinear MLPs enable weight-based mechanistic interpretability
    2024/10/10 by Michael Pearce, Thomas Dooms, Pearce, Michael T. +7 · 9 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Multimodal Machine Learning Applications #Natural Language Processing Techniques
  3. The Trifecta: Three simple techniques for training deeper Forward-Forward networks
    2023/11/29 by Thomas Dooms, Ing Jyh Tsang, Dooms, Thomas +3 · 3 citations
    Computer Science · Medicine · #68T07 #Advanced Neural Network Applications #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG)
  4. An Analysis of Human-centered Geolocation
    2017/07/10 by Kaili Wang, Yu-Hui Huang, Wang, Kaili +7 · 1 citation
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Video Surveillance and Tracking Methods #Visual Attention and Saliency Detection
  5. Modeling Visual Compatibility through Hierarchical Mid-level Elements
    2016/03/31 by José Oramas, Oramas, Jose, Tinne Tuytelaars +1 · 1 citation
    Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Multimodal Machine Learning Applications