Wenming Zheng

Computer Vision and Pattern Recognition · 2017–2021

A researcher in the Science corpus: 5 papers; trusts 271 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 72 citations into it
• Artificial Intelligence — 56 citations into it
• Experimental and Cognitive Psychology — 40 citations into it; #4,427 of 9,731 by trust here, #3,026 by citations
• Cognitive Neuroscience — 38 citations into it; #5,181 of 10,852 by trust here, #4,095 by citations
• Biomedical Engineering — 19 citations into it
• Model Architectures — 15 citations into it
• Graph Learning — 13 citations into it
• Human-Computer Interaction — 13 citations into it; #2,166 of 2,253 by trust here, #1,127 by citations

Whom Wenming Zheng trusts overall

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

1. Geoffrey E. Hinton
2. Wei-Long Zheng
3. Alex Krizhevsky
4. Kaiming He
5. L. Eon Bottou
6. Yoshua Bengio
7. Yann LeCun
8. Ilya Sutskever
9. Diederik P. Kingma
10. Alex Graves

Who trusts Wenming Zheng overall

1. Peixiang Zhong
2. Xiang Li
3. Y. Li
4. Yi Ding
5. Di Wang
6. Dongrui Wu
7. Xiaotong Gu
8. Nazmi Sofian Suhaimi
9. Wei-Bang Jiang
10. Chunyan Miao

Papers from Wenming Zheng's perspective

Ordered by how strongly the researchers Wenming Zheng 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• A Bi-Hemisphere Domain Adversarial Neural Network Model for EEG Emotion Recognition (2021) — 311 citations
• EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks (2020) — 1,382 citations
• A Novel Bi-Hemispheric Discrepancy Model for EEG Emotion Recognition (2019) — 325 citations
• Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition (2018) — 187 citations
• Spatial–Temporal Recurrent Neural Network for Emotion Recognition (2017) — 504 citations