Yehui Tang

Computer Vision and Pattern Recognition · 2019–2022

A researcher in the Science corpus: 8 papers; trusts 935 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 427 citations into it
• Artificial Intelligence — 339 citations into it
• Model Architectures — 149 citations into it
• Efficiency & Compression — 110 citations into it
• Optimization & Training — 42 citations into it
• Representation & Self-Supervised Learning — 32 citations into it
• Graph Learning — 23 citations into it
• Evaluation & Benchmarks — 19 citations into it

Whom Yehui Tang trusts overall

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

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

Who trusts Yehui Tang overall

1. Shumin Kong
2. Shan You
3. Kai Han
4. Xinhao Cai
5. Tianyu Guo

Papers from Yehui Tang's perspective

Ordered by how strongly the researchers Yehui Tang 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
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

• CMT: Convolutional Neural Networks Meet Vision Transformers (2021) — 951 citations
• A Survey on Vision Transformer (2020) — 3,751 citations
• Vision GNN: An Image is Worth Graph of Nodes (2022) — 633 citations
• GhostNetV2: Enhance Cheap Operation with Long-Range Attention (2022) — 579 citations
• Reborn Filters: Pruning Convolutional Neural Networks with Limited Data (2020) — 33 citations
• Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks (2020) — 41 citations
• Frequency Domain Compact 3D Convolutional Neural Networks (2020) — 32 citations
• Bringing Giant Neural Networks Down to Earth with Unlabeled Data (2019) — 11 citations