Shiqi Yu

Computer Vision and Pattern Recognition · 2006–2021

A researcher in the Science corpus: 6 papers; trusts 161 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 73 citations into it; #5,791 of 21,575 by trust here, #8,722 by citations
• Artificial Intelligence — 39 citations into it; #9,561 of 35,345 by trust here, #16,771 by citations
• Media Technology — 34 citations into it; #2,702 of 3,621 by trust here, #2,033 by citations
• Biomedical Engineering — 27 citations into it; #1,024 of 10,734 by trust here, #5,396 by citations
• Atmospheric Science — 22 citations into it; #3,367 of 4,804 by trust here, #3,198 by citations
• Model Architectures — 14 citations into it
• Human-Computer Interaction — 9 citations into it
• Optimization & Training — 7 citations into it

Whom Shiqi Yu trusts overall

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

1. Liang Wang
2. Geoffrey E. Hinton
3. Ju Han
4. Navneet Dalal
5. Tien-Ping Tan
6. Alex Krizhevsky
7. Kaiming He
8. Ralph Gross
9. Sepp Hochreiter
10. Yann LeCun

Who trusts Shiqi Yu overall

1. Khalid Bashir
2. Haruyuki Iwama
3. Zihao Mu
4. Lishan Qiao
5. Antitza Dantcheva
6. Torben Teepe
7. Beibei Lin
8. Tao A. Xiang
9. Xiaohui Yuan
10. Hanqing Chao

Papers from Shiqi Yu's perspective

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

Their papers

• A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition (2006) — 1,264 citations
• A Study on Gait-Based Gender Classification (2009) — 306 citations
• A model-based gait recognition method with body pose and human prior knowledge (2020) — 497 citations
• A survey: Deep learning for hyperspectral image classification with few labeled samples (2021) — 346 citations
• iLGaCo: Incremental Learning of Gait Covariate Factors (2020) — 7 citations
• Convolutional neural networks for hyperspectral image classification (2017) — 609 citations