Christoph Käding

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 7 citations into it

Whom Christoph Käding trusts overall

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

1. Philipp Krahenbuhl
2. Carl E. Rasmussen
3. Matthieu Guillaumin
4. Christopher K. I. Williams
5. Yangqing Jia
6. Vladlen Koltun
7. Geoffrey E. Hinton
8. Ross B. Girshick
9. Burr Settles
10. Alex Krizhevsky

Papers from Christoph Käding's perspective

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

Their papers

• Active learning and discovery of object categories in the presence of unnameable instances (2015) — 58 citations