Béatrice Cochener

Computer Vision and Pattern Recognition · 2008–2016

A researcher in the Science corpus: 4 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Béatrice Cochener trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Alex Krizhevsky
  2. Benjamin Graham

Papers from Béatrice Cochener's perspective

Ordered by how strongly the researchers Béatrice Cochener trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  3. Visualizing and Understanding Convolutional Networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Maxout Networks
  6. Gradient-based learning applied to document recognition
  7. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
  8. Learning Multiple Layers of Features from Tiny Images
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Going deeper with convolutions

Their papers