Jiagang Zhu

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 41 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jiagang Zhu trusts

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

  1. Kaiming He (in Computer Vision and Pattern Recognition)
  2. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  3. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  4. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  5. X. Zhang (in Computer Vision and Pattern Recognition)
  6. Piotr Doll'ar (in Computer Vision and Pattern Recognition)
  7. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  8. Jitendra Malik (in Computer Vision and Pattern Recognition)
  9. Karen Simonyan (in Computer Vision and Pattern Recognition)
  10. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)

Papers from Jiagang Zhu's perspective

Ordered by how strongly the researchers Jiagang Zhu 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. ImageNet Large Scale Visual Recognition Challenge
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  7. Dropout: a simple way to prevent neural networks from overfitting
  8. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  9. Gradient-based learning applied to document recognition
  10. Aggregated Residual Transformations for Deep Neural Networks

Their papers