Hong Kang

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hong Kang trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick
  3. Shaoqing Ren
  4. Geoffrey E. Hinton

Papers from Hong Kang's perspective

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

Their papers