John See

Computer Vision and Pattern Recognition · 2014–2020

A researcher in the Science corpus: 5 papers; trusts 349 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom John See trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick
  3. Karen Simonyan
  4. Tsung-Yi Lin
  5. Geoffrey E. Hinton
  6. Alex Krizhevsky
  7. Diederik P. Kingma
  8. Shaoqing Ren
  9. Andrew Zisserman
  10. Yann LeCun

Who trusts John See overall

  1. Xue Yang

Papers from John See's perspective

Ordered by how strongly the researchers John See 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Going deeper with convolutions

Their papers