Jingyong Su

Computer Vision and Pattern Recognition · 2014–2016

A researcher in the Science corpus: 5 papers; trusts 119 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 64 citations into it; #9,899 of 21,575 by trust here, #11,950 by citations
• Human-Computer Interaction — 22 citations into it
• Geometry and Topology — 17 citations into it; #4,377 of 7,422 by trust here, #3,228 by citations
• Artificial Intelligence — 14 citations into it; #15,922 of 35,345 by trust here, #18,586 by citations
• Biomedical Engineering — 14 citations into it; #2,719 of 10,734 by trust here, #5,809 by citations
• 3D Vision & Pose — 12 citations into it
• Representation & Self-Supervised Learning — 9 citations into it; #2,368 of 3,145 by trust here, #2,404 by citations

Whom Jingyong Su trusts overall

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

1. Anuj Srivastava
2. Huiling Le
3. Eric Klassen
4. Dimitri P. Bertsekas
5. Mirza Faisal Beg
6. Sebastian N. Kurtek
7. Omar Oreifej
8. Zicheng Liu
9. Wanqing Li
10. Lu Xia

Who trusts Jingyong Su overall

1. Boulbaba Ben Amor
2. Amor Ben Tanfous
3. Fei Han
4. Anuj Srivastava
5. Hassen Drira
6. Xiongtao Dai
7. Brian Reily
8. Raviteja Vemulapalli
9. Rushil Anirudh
10. William A. Hoff

Papers from Jingyong Su's perspective

Ordered by how strongly the researchers Jingyong Su 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Elastic functional coding of human actions: From vector-fields to latent variables (2015) — 96 citations
• Action Recognition Using Rate-Invariant Analysis of Skeletal Shape Trajectories (2016) — 215 citations
• Statistical analysis of trajectories on Riemannian manifolds: Bird migration, hurricane tracking and video surveillance (2014) — 132 citations
• Elastic Functional Coding of Riemannian Trajectories (2016) — 54 citations
• Rate-Invariant Analysis of Trajectories on Riemannian Manifolds with Application in Visual Speech Recognition (2014) — 46 citations