Zhen Cui

Computer Vision and Pattern Recognition · 2017–2021

A researcher in the Science corpus: 7 papers; trusts 759 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 155 citations into it; #15,627 of 21,575 by trust here, #9,079 by citations
• Artificial Intelligence — 78 citations into it
• Experimental and Cognitive Psychology — 40 citations into it; #4,426 of 9,731 by trust here, #3,026 by citations
• Cognitive Neuroscience — 38 citations into it; #5,180 of 10,852 by trust here, #4,095 by citations
• Model Architectures — 25 citations into it
• Biomedical Engineering — 20 citations into it
• Representation & Self-Supervised Learning — 20 citations into it
• Aerospace Engineering — 14 citations into it

Whom Zhen Cui trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Karen Simonyan
7. Yann LeCun
8. Diederik P. Kingma
9. Ilya Sutskever
10. Jia Deng

Who trusts Zhen Cui overall

1. Simon Vandenhende
2. Peixiang Zhong
3. Menelaos Kanakis
4. Luc Van Gool
5. Stamatios Georgoulis
6. Xiang Li
7. Y. Li
8. Yi Ding
9. Seyed Mehran Kazemi

Papers from Zhen Cui's perspective

Ordered by how strongly the researchers Zhen Cui 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

• Pattern-Affinitive Propagation Across Depth, Surface Normal and Semantic Segmentation (2019) — 322 citations
• Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation (2018) — 234 citations
• 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