Georges Baatz

Computer Vision and Pattern Recognition · 2010

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Georges Baatz trusts overall

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

  1. Jana Kosecka
  2. David G. Lowe
  3. Radford M. Neal
  4. Christopher Evans
  5. David Nistér
  6. Henrik Stewénius
  7. Grant Schindler

Who trusts Georges Baatz overall

  1. Tobias Weyand
  2. Bastian Leibe

Papers from Georges Baatz's perspective

Ordered by how strongly the researchers Georges Baatz trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Distinctive Image Features from Scale-Invariant Keypoints
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. ImageNet: A large-scale hierarchical image database
  5. ImageNet Large Scale Visual Recognition Challenge
  6. Scalable Recognition with a Vocabulary Tree
  7. Gradient-based learning applied to document recognition
  8. Long Short-Term Memory
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Going deeper with convolutions

Their papers