Cong Yang

Computer Vision and Pattern Recognition · with Chen · 2020

A researcher in the Science corpus: 1 paper; trusts 69 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Cong Yang trusts overall

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

  1. Kaiming He

Papers from Cong Yang's perspective

Ordered by how strongly the researchers Cong Yang 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: A large-scale hierarchical image database
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Microsoft COCO: Common Objects in Context
  5. ImageNet classification with deep convolutional neural networks
  6. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
  7. Gradient-based learning applied to document recognition
  8. Going deeper with convolutions
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers