Sheng Jin

Computer Vision and Pattern Recognition · with Chen · 2019

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Sheng Jin trusts

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

  1. Trevor Darrell (in Computer Vision and Pattern Recognition)
  2. Ross B. Girshick (in Computer Vision and Pattern Recognition)

Papers from Sheng Jin's perspective

Ordered by how strongly the researchers Sheng Jin 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. ImageNet: A large-scale hierarchical image database
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Going deeper with convolutions
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Learning Multiple Layers of Features from Tiny Images

Their papers