Han Shu

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 108 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 76 citations into it
• Artificial Intelligence — 42 citations into it
• Efficiency & Compression — 34 citations into it

Whom Han Shu trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Song Han
5. Yoshua Bengio
6. Karen Simonyan
7. Yann LeCun
8. Evan Shelhamer
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Han Shu overall

1. Abdul Jabbar
2. Yonggan Fu
3. Jie Gui
4. Kai Han
5. Muyang Li
6. Yunhe Wang
7. Xi Li

Papers from Han Shu's perspective

Ordered by how strongly the researchers Han Shu 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Co-Evolutionary Compression for Unpaired Image Translation (2019) — 93 citations
• Frequency Domain Compact 3D Convolutional Neural Networks (2020) — 32 citations
• Distilling portable Generative Adversarial Networks for Image Translation (2020) — 89 citations