Julius Keyl

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Julius Keyl trusts overall

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

  1. Kaiming He
  2. Ross B. Girshick
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Tsung-Yi Lin

Papers from Julius Keyl's perspective

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

Their papers