Jing Ye

Computer Vision and Pattern Recognition · with Liu · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 69 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jing Ye trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick
  3. Diederik P. Kingma
  4. Geoffrey E. Hinton
  5. Shaoqing Ren
  6. Alex Krizhevsky
  7. Yoshua Bengio
  8. Yann LeCun
  9. Xiaozhi Chen
  10. Karen Simonyan

Papers from Jing Ye's perspective

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

Their papers