Matthew Johnson-Roberson

Computer Vision and Pattern Recognition · 2004–2017

A researcher in the Science corpus: 3 papers; trusts 59 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Matthew Johnson-Roberson trusts overall

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

  1. Hao Su
  2. Geoffrey E. Hinton
  3. Antonio Torralba
  4. Andreas Geiger
  5. Kaiming He
  6. Alex Krizhevsky
  7. Yann LeCun
  8. Ross B. Girshick
  9. Yoshua Bengio
  10. Karen Simonyan

Who trusts Matthew Johnson-Roberson overall

  1. Sergey I. Nikolenko
  2. Bichen Wu
  3. Zhenwei He
  4. Lukas Liebel
  5. Luca Ciampi
  6. Braden Hurl
  7. Giuseppe Amato
  8. Kuniaki Saito
  9. Tao Wang
  10. Qi Wang

Papers from Matthew Johnson-Roberson's perspective

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

Their papers