Tie Liu

Computer Vision and Pattern Recognition · with Guan · 2017

A researcher in the Science corpus: 1 paper; trusts 27 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tie Liu trusts overall

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

  1. Kaiming He
  2. Gregory K. Wallace
  3. Chao Dong
  4. Frank Bossen
  5. Alex Krizhevsky

Papers from Tie Liu's perspective

Ordered by how strongly the researchers Tie Liu 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. Fully convolutional networks for semantic segmentation
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. ImageNet Large Scale Visual Recognition Challenge
  7. ImageNet: A large-scale hierarchical image database
  8. Going deeper with convolutions
  9. Long Short-Term Memory
  10. Visualizing and Understanding Convolutional Networks

Their papers