Jun Shi

Computer Vision and Pattern Recognition · 2 papers · 2019

A researcher in the Science corpus: 2 papers; trusts 106 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun Shi trusts overall

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

  1. Chao Dong
  2. Kaiming He
  3. Jiwon Kim
  4. Geoffrey E. Hinton
  5. Diederik P. Kingma
  6. Jae-Seok Choi
  7. Ying Tai
  8. Alex Krizhevsky
  9. Chen Change Loy
  10. Kai Zhang

Papers from Jun Shi's perspective

Ordered by how strongly the researchers Jun Shi 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. Gradient-based learning applied to document recognition
  5. ImageNet Large Scale Visual Recognition Challenge
  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. Attention is All you Need (Neural Information Processing Systems)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers