Reiner Birkl

Computer Vision and Pattern Recognition · 2023

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Reiner Birkl trusts overall

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

  1. René Ranftl
  2. Moritz Menze
  3. Zhengqi Li
  4. Mike Roberts
  5. Shuran Song
  6. Nathan Silberman
  7. Geoffrey E. Hinton
  8. Kaiming He
  9. Shariq Farooq Bhat
  10. Alex Krizhevsky

Papers from Reiner Birkl's perspective

Ordered by how strongly the researchers Reiner Birkl 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. Attention is All you Need (Neural Information Processing Systems)
  5. ImageNet: A large-scale hierarchical image database
  6. Gradient-based learning applied to document recognition
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Long Short-Term Memory
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers