Ying Shen

Computer Vision and Pattern Recognition · with Li · 2014

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Ying Shen trusts overall

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

  1. Zhou Wang

Who trusts Ying Shen overall

  1. Ke Gu
  2. Jongyoo Kim
  3. Wencheng Wang
  4. Ekta Prashnani
  5. Rafael Reisenhofer
  6. Albert Y. Kim
  7. Weisi Lin
  8. Shiqi Wang
  9. Kede Ma
  10. Xiongkuo Min

Papers from Ying Shen's perspective

Ordered by how strongly the researchers Ying Shen 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. ImageNet classification with deep convolutional neural networks
  4. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Distinctive Image Features from Scale-Invariant Keypoints
  7. Going deeper with convolutions
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers