Thomas Lansdall-Welfare

Computer Vision and Pattern Recognition · 2015–2018

A researcher in the Science corpus: 4 papers; trusts 285 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Lansdall-Welfare trusts overall

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

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

Who trusts Thomas Lansdall-Welfare overall

  1. Shruti Bhargava

Papers from Thomas Lansdall-Welfare's perspective

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

Their papers