Thomas Köhler

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Köhler trusts overall

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

  1. Yann LeCun
  2. Christian Szegedy
  3. François Chollet

Papers from Thomas Köhler's perspective

Ordered by how strongly the researchers Thomas Köhler 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. Going deeper with convolutions
  3. ImageNet Large Scale Visual Recognition Challenge
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Dropout: a simple way to prevent neural networks from overfitting
  6. ImageNet classification with deep convolutional neural networks
  7. Rethinking the Inception Architecture for Computer Vision
  8. CNN Features Off-the-Shelf: An Astounding Baseline for Recognition
  9. Gradient-based learning applied to document recognition
  10. Long Short-Term Memory

Their papers