Jun Han

Computer Vision and Pattern Recognition · with Huang · 2019

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun Han trusts overall

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

  1. Karen Simonyan
  2. Qiuhong Ke
  3. Andrew Zisserman
  4. Eshed Ohn-Bar
  5. Gurkirt Singh
  6. Liliana Lo Presti
  7. Geoffrey E. Hinton
  8. Yann LeCun
  9. Alex Krizhevsky
  10. Amir Shahroudy

Papers from Jun Han's perspective

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

Their papers