Françoise J. Prêteux

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 72 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Françoise J. Prêteux trusts overall

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

  1. Geoffrey E. Hinton
  2. Karen Simonyan
  3. Ross B. Girshick
  4. Kaiming He
  5. Shaoqing Ren
  6. Andrew Zisserman
  7. Alex Krizhevsky
  8. Tomas Mikolov

Papers from Françoise J. Prêteux's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. ImageNet: A large-scale hierarchical image database
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Going deeper with convolutions

Their papers