Yang Zou

Computer Vision and Pattern Recognition · with Huang · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 707 researchers and is trusted by 108 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 124 citations into it; #3,136 of 21,575 by trust here, #3,955 by citations
• Artificial Intelligence — 90 citations into it; #4,575 of 35,345 by trust here, #5,281 by citations
• Representation & Self-Supervised Learning — 35 citations into it; #2,702 of 3,145 by trust here, #1,781 by citations
• Evaluation & Benchmarks — 21 citations into it
• Model Architectures — 10 citations into it
• Aerospace Engineering — 7 citations into it
• Statistical Learning Theory — 5 citations into it
• Signal Processing — 5 citations into it

Whom Yang Zou trusts overall

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

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

Who trusts Yang Zou overall

1. Lukas Hoyer
2. Dengxin Dai
3. Yahao Liu
4. Christos Sakaridis
5. Luc Van Gool
6. Luke Melas-Kyriazi
7. Yanchao Yang
8. Kuniaki Saito
9. Jianfeng Feng
10. Wilhelm Tranheden

Papers from Yang Zou's perspective

Ordered by how strongly the researchers Yang Zou 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. Gradient-based learning applied to document recognition
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

• Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-training (2018) — 1,499 citations
• Confidence Regularized Self-Training (2019) — 917 citations
• Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection (2020) — 146 citations
• Sliced Wasserstein Kernels for Probability Distributions (2015) — 182 citations