Jun Chen

Computer Vision and Pattern Recognition · with Liu · 2021

A researcher in the Science corpus: 1 paper; trusts 33 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun Chen trusts overall

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

  1. Diederik P. Kingma
  2. Jessica J. Fridrich
  3. Kaiming He
  4. Babak Mahdian
  5. Thomas Gloe

Papers from Jun Chen's perspective

Ordered by how strongly the researchers Jun Chen trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Attention is All you Need (Neural Information Processing Systems)
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. ImageNet classification with deep convolutional neural networks
  5. Microsoft COCO: Common Objects in Context
  6. Gradient-based learning applied to document recognition
  7. Going deeper with convolutions
  8. ImageNet: A large-scale hierarchical image database
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers