Feng Jin

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Feng Jin trusts overall

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

  1. Richard Szeliski
  2. Zhengyou Zhang
  3. Kaiming He
  4. Mingmin Zhao
  5. Leonid Pishchulin
  6. Eldar Insafutdinov
  7. Ross B. Girshick
  8. Alex Krizhevsky
  9. Geoffrey E. Hinton
  10. Zhe Cao

Papers from Feng Jin's perspective

Ordered by how strongly the researchers Feng Jin 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 classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. ImageNet: A large-scale hierarchical image database
  8. Going deeper with convolutions
  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