F. Prayer

Computer Vision and Pattern Recognition · 2020

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 — 13 citations into it

Whom F. Prayer trusts overall

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

1. Boris Polyak
2. Sergey Ioffe
3. Kaiming He
4. Christian Szegedy
5. Olaf Ronneberger
6. Liang-Chieh Chen

Papers from F. Prayer's perspective

Ordered by how strongly the researchers F. Prayer 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet Large Scale Visual Recognition Challenge
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem (2020) — 570 citations