Scott Lee

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Scott Lee trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Kaiming He

Papers from Scott Lee's perspective

Ordered by how strongly the researchers Scott Lee 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: A large-scale hierarchical image database
  3. Learning Multiple Layers of Features from Tiny Images
  4. ImageNet classification with deep convolutional neural networks
  5. Distilling the Knowledge in a Neural Network (arXiv.org)
  6. Gradient-based learning applied to document recognition
  7. Visualizing and Understanding Convolutional Networks
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Going deeper with convolutions

Their papers