Hui Ji

Computer Vision and Pattern Recognition · with Chen · 2020

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hui Ji trusts

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

  1. Michael Elad (in Computer Vision and Pattern Recognition)
  2. Andrea Vedaldi (in Computer Vision and Pattern Recognition)
  3. Michal Aharon (in Computer Vision and Pattern Recognition)
  4. Lei Zhang (in Computer Vision and Pattern Recognition)
  5. Joshua D. Batson (in Computer Vision and Pattern Recognition)
  6. Loic A. Royer (in Computer Vision and Pattern Recognition)
  7. Wangmeng Zuo (in Computer Vision and Pattern Recognition)
  8. Victor S. Lempitsky (in Computer Vision and Pattern Recognition)
  9. Kai Zhang (in Computer Vision and Pattern Recognition)

Papers from Hui Ji's perspective

Ordered by how strongly the researchers Hui Ji trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Dropout: a simple way to prevent neural networks from overfitting
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Going deeper with convolutions
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Learning Multiple Layers of Features from Tiny Images

Their papers