Shengen Yan

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 297 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 77 citations into it; #19,808 of 21,575 by trust here, #6,737 by citations
• Artificial Intelligence — 55 citations into it
• Optimization & Training — 25 citations into it
• Efficiency & Compression — 13 citations into it
• Model Architectures — 10 citations into it
• Media Technology — 6 citations into it

Whom Shengen Yan trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Andrew Zisserman
5. Karen Simonyan
6. Christian Szegedy
7. Ross B. Girshick
8. Ilya Sutskever
9. Yann LeCun
10. Yoshua Bengio

Who trusts Shengen Yan overall

1. Yanming Guo
2. Suyog Gupta
3. Aysegul Dundar
4. Luke Taylor
5. Luke Taylor
6. Fisher Yu
7. Zhenhua Wang
8. Khaled Alomar
9. Yi-Zhou Lin
10. Forrest N. Iandola

Papers from Shengen Yan's perspective

Ordered by how strongly the researchers Shengen Yan 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. 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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Deep Image: Scaling up Image Recognition (2015) — 385 citations
• Evaluating Fast Algorithms for Convolutional Neural Networks on FPGAs (2020) — 311 citations
• Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes (2019) — 72 citations