Nathan W. Fuller

Computer Vision and Pattern Recognition · 2014

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nathan W. Fuller trusts overall

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

  1. Andrew Zisserman
  2. Victor S. Lempitsky
  3. Antoni B. Chan
  4. Atousa Torabi
  5. Haroon Idrees
  6. Jürg Portmann

Papers from Nathan W. Fuller's perspective

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

Their papers