Michael Engstler

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 15 citations into it
• Model Architectures — 6 citations into it

Whom Michael Engstler trusts overall

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

1. Karen Simonyan
2. Yann LeCun
3. Navneet Dalal
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Andrew Zisserman

Papers from Michael Engstler's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. ImageNet: A large-scale hierarchical image database
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Histograms of oriented gradients for human detection
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Advanced Steel Microstructural Classification by Deep Learning Methods (2017) — 429 citations