Bernhard Egger

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 16 citations into it

Whom Bernhard Egger trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Karen Simonyan
4. Geoffrey E. Hinton

Papers from Bernhard Egger's perspective

Ordered by how strongly the researchers Bernhard Egger 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. Learning Multiple Layers of Features from Tiny Images
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Densely Connected Convolutional Networks
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• C-GOOD: C-code Generation Framework for Optimized On-device Deep Learning (2018) — 27 citations