Hayko Riemenschneider

Computer Vision and Pattern Recognition · 2012–2015

A researcher in the Science corpus: 6 papers; trusts 577 researchers and is trusted by 35 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 115 citations into it; #4,957 of 21,575 by trust here, #5,806 by citations
• Aerospace Engineering — 18 citations into it
• Computer Graphics and Computer-Aided Design — 15 citations into it
• Artificial Intelligence — 10 citations into it
• Computational Mechanics — 10 citations into it; #9,584 of 10,001 by trust here, #4,937 by citations
• Media Technology — 10 citations into it
• Geology — 9 citations into it
• Environmental Engineering — 7 citations into it; #4,499 of 5,479 by trust here, #2,998 by citations

Whom Hayko Riemenschneider trusts overall

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

1. David G. Lowe
2. Yuri Boykov
3. Kaiming He
4. Jitendra Malik
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Cordelia Schmid
8. Ross B. Girshick
9. Jamie Shotton
10. Andrew Zisserman

Who trusts Hayko Riemenschneider overall

1. Ziyu Zhang
2. Christopher Bongsoo Choy
3. Gernot Riegler
4. Sanja Fidler
5. Scott Drew Pendleton
6. Andelo Martinovic
7. Ankit Goyal
8. Paul Wohlhart
9. Hang Su
10. Raquel Urtasun

Papers from Hayko Riemenschneider's perspective

Ordered by how strongly the researchers Hayko Riemenschneider 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
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

• Creating Summaries from User Videos (2014) — 826 citations
• Learning Where to Classify in Multi-view Semantic Segmentation (2014) — 120 citations
• The Interestingness of Images (2013) — 203 citations
• Hough Regions for Joining Instance Localization and Segmentation (2012) — 31 citations
• 3D all the way: Semantic segmentation of urban scenes from start to end in 3D (2015) — 145 citations
• The Synthesizability of Texture Examples (2014) — 45 citations