Jin Zhou

Computer Vision and Pattern Recognition · with Wang · 2018

A researcher in the Science corpus: 1 paper; trusts 34 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jin Zhou trusts

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

  1. Yann LeCun (in Computer Vision and Pattern Recognition)
  2. Kaiming He (in Computer Vision and Pattern Recognition)
  3. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  4. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  5. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  6. Xiaoou Tang (in Computer Vision and Pattern Recognition)
  7. X. Zhang (in Computer Vision and Pattern Recognition)
  8. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  9. Xiaogang Wang (in Computer Vision and Pattern Recognition)
  10. Karen Simonyan (in Computer Vision and Pattern Recognition)

Papers from Jin Zhou's perspective

Ordered by how strongly the researchers Jin Zhou 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. Going deeper with convolutions
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Dimensionality Reduction by Learning an Invariant Mapping
  6. Caffe: Convolutional Architecture for Fast Feature Embedding
  7. Learning a similarity metric discriminatively, with application to face verification
  8. Aggregated Residual Transformations for Deep Neural Networks
  9. FaceNet: A unified embedding for face recognition and clustering
  10. Gradient-based learning applied to document recognition

Their papers