J. Fritsch

Computer Vision and Pattern Recognition · 2013–2014

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 7 citations into it; #8,080 of 21,575 by trust here, #11,950 by citations

Whom J. Fritsch trusts overall

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

1. Andreas Geiger
2. Philip Lenz
3. Frank Moosmann
4. Derek Hoiem
5. Raquel Urtasun
6. Christian Wojek

Who trusts J. Fritsch overall

1. Rui Fan
2. Chase J. Gaudet
3. Xiaolong Liu
4. Dan Barnes
5. Gabriel L. Oliveira
6. Francisco Angel Moreno
7. Joel Janai
8. Hengli Wang
9. Marvin T. T. Teichmann
10. Panqu Wang

Papers from J. Fritsch's perspective

Ordered by how strongly the researchers J. Fritsch 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. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• A new performance measure and evaluation benchmark for road detection algorithms (2013) — 687 citations
• Robots Show Us How to Teach Them: Feedback from Robots Shapes Tutoring Behavior during Action Learning (2014) — 59 citations