Zewen Li

Computer Vision and Pattern Recognition · with Liu · 2020

A researcher in the Science corpus: 1 paper; trusts 426 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 119 citations into it; #20,060 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 75 citations into it; #32,718 of 35,345 by trust here, #25,809 by citations
• Model Architectures — 37 citations into it; #2,075 of 2,278 by trust here, #1,976 by citations
• Optimization & Training — 17 citations into it
• Signal Processing — 16 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Electrical and Electronic Engineering — 7 citations into it
• Aerospace Engineering — 6 citations into it

Whom Zewen Li trusts overall

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

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

Who trusts Zewen Li overall

1. Mohammad Mustafa Taye
2. Xizhou Zhu
3. K. Liang

Papers from Zewen Li's perspective

Ordered by how strongly the researchers Zewen Li 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. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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

• A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects (2020) — 4,320 citations