Xiao Xiang Zhu

Computer Vision and Pattern Recognition · with Mou · 2022–2023

A researcher in the Science corpus: 5 papers; trusts 524 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 143 citations into it; #14,499 of 21,575 by trust here, #17,757 by citations
• Artificial Intelligence — 102 citations into it; #26,401 of 35,345 by trust here, #25,809 by citations
• Representation & Self-Supervised Learning — 81 citations into it
• Media Technology — 58 citations into it; #2,547 of 3,621 by trust here, #2,706 by citations
• Atmospheric Science — 27 citations into it
• Ecology — 14 citations into it
• Model Architectures — 12 citations into it
• Ocean Engineering — 10 citations into it

Whom Xiao Xiang Zhu trusts overall

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

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

Who trusts Xiao Xiang Zhu overall

1. Valerio Marsocci

Papers from Xiao Xiang Zhu's perspective

Ordered by how strongly the researchers Xiao Xiang 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. ImageNet: A large-scale hierarchical image database
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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

• Semi-supervised bidirectional alignment for Remote Sensing cross-domain scene classification (2023) — 69 citations
• Unsupervised Single-Scene Semantic Segmentation for Earth Observation (2022) — 41 citations
• Self Supervised Learning for Few Shot Hyperspectral Image Classification (2022) — 14 citations
• DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation (2022) — 141 citations
• Self-Supervised Learning in Remote Sensing: A review (2022) — 357 citations