K. Moore

Computer Vision and Pattern Recognition · Cell · 2017–2021

A researcher in the Science corpus: 6 papers; trusts 134 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom K. Moore trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Alex Krizhevsky
  6. Karen Simonyan
  7. Yann LeCun
  8. Yoshua Bengio
  9. Andrew Zisserman
  10. Ilya Sutskever

Papers from K. Moore's perspective

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

Their papers