Jun Liang

Computer Vision and Pattern Recognition · with Cao · 2018

A researcher in the Science corpus: 1 paper; trusts 81 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun Liang trusts overall

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

  1. Ross B. Girshick
  2. Kaiming He
  3. Karen Simonyan
  4. Piotr Doll'ar
  5. Alex Krizhevsky
  6. Andrew Zisserman
  7. Geoffrey E. Hinton
  8. Yann LeCun
  9. Shaoqing Ren
  10. Yoshua Bengio

Papers from Jun Liang's perspective

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

Their papers