Kang Zhang

Computer Vision and Pattern Recognition · with Zhang · 2022

A researcher in the Science corpus: 2 papers; trusts 302 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 99 citations into it
• Artificial Intelligence — 92 citations into it
• Representation & Self-Supervised Learning — 61 citations into it
• Large Language Models — 9 citations into it

Whom Kang Zhang trusts overall

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

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

Papers from Kang Zhang's perspective

Ordered by how strongly the researchers Kang Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo (2022) — 74 citations
• A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond (2022) — 102 citations