B. Egger

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom B. Egger trusts overall

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

  1. Volker Blanz
  2. Thomas Vetter
  3. Justus Thies
  4. James Booth
  5. Luan Tran
  6. Chen Cao
  7. Brian Amberg
  8. Michael Zollhöfer
  9. Pascal Paysan
  10. Geoffrey E. Hinton

Who trusts B. Egger overall

  1. Yang Hong
  2. Weihao Xia

Papers from B. Egger's perspective

Ordered by how strongly the researchers B. Egger 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 classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. GENERATIVE ADVERSARIAL NETS
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Going deeper with convolutions

Their papers