Qing Zhu

Computer Vision and Pattern Recognition · with Li · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 341 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 139 citations into it
• Artificial Intelligence — 99 citations into it
• Representation & Self-Supervised Learning — 73 citations into it
• Media Technology — 43 citations into it
• Multimodal Learning — 11 citations into it
• Signal Processing — 9 citations into it

Whom Qing Zhu trusts overall

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

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

Papers from Qing Zhu's perspective

Ordered by how strongly the researchers Qing Zhu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Self-Supervised Remote Sensing Feature Learning: Learning Paradigms, Challenges, and Future Works (2022) — 91 citations
• Global and Local Contrastive Self-Supervised Learning for Semantic Segmentation of HR Remote Sensing Images (2021) — 153 citations