Daniel Gehrig

Computer Vision and Pattern Recognition · 2018–2024

A researcher in the Science corpus: 5 papers; trusts 194 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Daniel Gehrig trusts overall

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

  1. Alex Zihao Zhu
  2. Diederik P. Kingma
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Henri Rebecq
  6. Kaiming He
  7. Ross B. Girshick
  8. Jia Deng
  9. Yann LeCun
  10. Olga Russakovsky

Who trusts Daniel Gehrig overall

  1. Guillermo Gallego
  2. Henri Rebecq
  3. Tobi Delbruck
  4. Yuhuang Hu
  5. Davide Scaramuzza
  6. René Ranftl
  7. Etienne Perot
  8. Shih-Chii Liu
  9. Garrick Orchard
  10. Vladlen Koltun

Papers from Daniel Gehrig's perspective

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

Their papers