Joseph G. Lambourne

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Joseph G. Lambourne trusts overall

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

  1. Diederik P. Kingma
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Sergey Ioffe
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Christian Szegedy
  8. Dekang Lin
  9. Jimmy Ba
  10. Yann LeCun

Papers from Joseph G. Lambourne's perspective

Ordered by how strongly the researchers Joseph G. Lambourne 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. ImageNet classification with deep convolutional neural networks
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. ImageNet: A large-scale hierarchical image database
  7. Long Short-Term Memory
  8. Gradient-based learning applied to document recognition
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Et al

Their papers