Mo Shan

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Mo Shan trusts overall

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

  1. Nitish Srivastava
  2. Patrice Y. Simard
  3. Hao Su
  4. Max Jaderberg
  5. Karen Simonyan
  6. Ruslan Salakhutdinov
  7. Geoffrey E. Hinton
  8. Andrew Zisserman
  9. Alex Krizhevsky
  10. Elman Mansimov

Papers from Mo Shan's perspective

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

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

Their papers