Joe Mathai

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Joe Mathai trusts overall

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

  1. Kaiming He
  2. Mohammad Rostami
  3. Alex Krizhevsky
  4. Yaojie Liu
  5. Geoffrey E. Hinton
  6. Amin Jourabloo
  7. R. M. French
  8. Zhengyou Zhang
  9. Anthony V. Robins
  10. Ilya Sutskever

Papers from Joe Mathai's perspective

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

Their papers