Lita Yang

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Lita Yang trusts overall

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

  1. Yann LeCun
  2. Geoffrey E. Hinton
  3. Song Han
  4. Alex Krizhevsky
  5. Matthew D. Zeiler
  6. Christian Szegedy
  7. Kaiming He
  8. X. Zhang
  9. Yoshua Bengio
  10. Kyuyeon Hwang

Papers from Lita Yang's perspective

Ordered by how strongly the researchers Lita Yang 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. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  7. Going deeper with convolutions
  8. Learning Multiple Layers of Features from Tiny Images
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers