Chengzhou Tang

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 497 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

Whom Chengzhou Tang trusts overall

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

  1. Kaiming He
  2. Diederik P. Kingma
  3. David Nistér
  4. Geoffrey E. Hinton
  5. Alex Krizhevsky
  6. David Eigen
  7. Ross B. Girshick
  8. Andreas Geiger
  9. Rob Fergus
  10. Sepp Hochreiter

Who trusts Chengzhou Tang overall

  1. Zachary Teed
  2. Jia Deng
  3. Yue Wang
  4. Peter Karkus
  5. Jiayu Yang
  6. Shuzhe Wang
  7. Xuan Luo
  8. Jiaming Sun
  9. Jianyuan Wang
  10. Haofei Xu

Papers from Chengzhou Tang's perspective

Ordered by how strongly the researchers Chengzhou Tang 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. Gradient-based learning applied to document recognition
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  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