Pu Lu

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Pu Lu trusts overall

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

  1. Kaiming He
  2. Baoguang Shi
  3. Ross B. Girshick
  4. Xiang Bai
  5. Geoffrey E. Hinton
  6. Alex Krizhevsky
  7. Cong Yao
  8. Tsung-Yi Lin
  9. Shaoqing Ren
  10. Karen Simonyan

Papers from Pu Lu's perspective

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

Their papers