Kevin Foster

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kevin Foster trusts overall

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

  1. François Chollet
  2. Heiko Hirschmüller
  3. Daniel Scharstein
  4. Moritz Menze
  5. Liang-Chieh Chen
  6. Kaiming He
  7. Gao Huang
  8. Geoffrey E. Hinton
  9. Tsung-Yi Lin
  10. Alex Krizhevsky

Papers from Kevin Foster's perspective

Ordered by how strongly the researchers Kevin Foster 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. Gradient-based learning applied to document recognition
  4. ImageNet: A large-scale hierarchical image database
  5. Microsoft COCO: Common Objects in Context
  6. ImageNet Large Scale Visual Recognition Challenge
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Long Short-Term Memory
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Going deeper with convolutions

Their papers