Jan Knopp

Computer Vision and Pattern Recognition · 2010–2015

A researcher in the Science corpus: 3 papers; trusts 403 researchers and is trusted by 52 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 65 citations into it; #4,179 of 21,575 by trust here, #7,340 by citations
• Aerospace Engineering — 18 citations into it; #1,054 of 6,421 by trust here, #1,665 by citations
• Information Retrieval & Search — 11 citations into it
• Computational Mechanics — 8 citations into it; #7,454 of 10,001 by trust here, #4,315 by citations
• Artificial Intelligence — 7 citations into it
• Geology — 7 citations into it
• Computer Graphics and Computer-Aided Design — 5 citations into it
• Environmental Engineering — 5 citations into it; #4,500 of 5,479 by trust here, #2,998 by citations

Whom Jan Knopp trusts overall

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

1. Josef Sivic
2. Andrew Zisserman
3. David G. Lowe
4. Herv'e J'egou
5. Yuri Boykov
6. Antonio Torralba
7. Geoffrey E. Hinton
8. Alex Krizhevsky
9. Kaiming He
10. Ross B. Girshick

Who trusts Jan Knopp overall

1. Tobias Weyand
2. Samuele Salti
3. Amir Zamir
4. Relja Arandjelovi'c
5. Charles Ruizhongtai Qi
6. Hyo Jin Kim
7. Song Cao
8. Yu-Gang Jiang
9. Bastian Leibe
10. Shuran Song

Papers from Jan Knopp's perspective

Ordered by how strongly the researchers Jan Knopp 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Hough Transform and 3D SURF for Robust Three Dimensional Classification (2010) — 388 citations
• Avoiding Confusing Features in Place Recognition (2010) — 249 citations
• 3D all the way: Semantic segmentation of urban scenes from start to end in 3D (2015) — 145 citations