Yong Du

Computer Vision and Pattern Recognition · with Wang · 2015–2017

A researcher in the Science corpus: 4 papers; trusts 438 researchers and is trusted by 215 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 117 citations into it; #2,321 of 21,575 by trust here, #3,313 by citations
• Human-Computer Interaction — 45 citations into it; #705 of 2,253 by trust here, #1,161 by citations
• Artificial Intelligence — 36 citations into it; #1,712 of 35,345 by trust here, #5,317 by citations
• Biomedical Engineering — 31 citations into it; #39 of 10,734 by trust here, #1,283 by citations
• Model Architectures — 22 citations into it; #151 of 2,278 by trust here, #517 by citations
• Control and Systems Engineering — 14 citations into it; #6,631 of 8,257 by trust here, #5,784 by citations
• Signal Processing — 13 citations into it
• Natural Language Processing — 12 citations into it

Whom Yong Du trusts overall

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

1. Alex Graves
2. Sepp Hochreiter
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ilya Sutskever
6. Yoshua Bengio
7. J. Urgen Schmidhuber
8. Yann LeCun
9. Fengjun Lv
10. Kaiming He

Who trusts Yong Du overall

1. Jun Liu
2. Pichao Wang
3. Mengyuan Liu
4. Amir Shahroudy
5. Pengfei Zhang
6. Wanqing Li
7. Qiuhong Ke
8. Hossein Rahmani
9. Cuiling Lan
10. Lei Shi

Papers from Yong Du's perspective

Ordered by how strongly the researchers Yong Du 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. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Hierarchical recurrent neural network for skeleton based action recognition (2015) — 2,061 citations
• Facial Expression Recognition Based on Deep Evolutional Spatial-Temporal Networks (2017) — 426 citations
• Skeleton based action recognition with convolutional neural network (2015) — 436 citations
• Representation Learning of Temporal Dynamics for Skeleton-Based Action Recognition (2016) — 147 citations