Tao Huang

Computer Vision and Pattern Recognition · The Innovation · 2020–2024

A researcher in the Science corpus: 5 papers; trusts 385 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tao Huang trusts overall

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

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

Who trusts Tao Huang overall

  1. Weihao Yu
  2. Xinchao Wang

Papers from Tao Huang's perspective

Ordered by how strongly the researchers Tao Huang 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. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Gradient-based learning applied to document recognition
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Going deeper with convolutions

Their papers