Ming Xu

Computer Vision and Pattern Recognition · with Fischer · 2021

A researcher in the Science corpus: 1 paper; trusts 84 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ming Xu trusts overall

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

  1. Andrew Zisserman
  2. Josef Sivic
  3. Karen Simonyan
  4. David G. Lowe
  5. Relja Arandjelovi'c
  6. Akihiko Torii
  7. Herv'e J'egou
  8. Christopher Evans
  9. Geoffrey E. Hinton
  10. Alex Krizhevsky

Papers from Ming Xu's perspective

Ordered by how strongly the researchers Ming Xu 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Gradient-based learning applied to document recognition
  7. Attention is All you Need (Neural Information Processing Systems)
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Going deeper with convolutions
  10. Long Short-Term Memory

Their papers