Y. Wu

Computer Vision and Pattern Recognition · with Shi · 2019–2022

A researcher in the Science corpus: 3 papers; trusts 137 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 120 citations into it
• Artificial Intelligence — 73 citations into it
• Generative Models — 28 citations into it
• Optimization & Training — 13 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Y. Wu trusts overall

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

1. Alex Krizhevsky
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Kaiming He
5. James Martens
6. Diederik P. Kingma
7. Jeff Donahue
8. Yann LeCun
9. Shun-ichi Amari
10. Max Welling

Who trusts Y. Wu overall

1. Mingu Kang
2. Zhengli Zhao
3. Jaesik Park
4. Michael Arbel

Papers from Y. Wu's perspective

Ordered by how strongly the researchers Y. Wu 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• LOGAN: Latent Optimisation for Generative Adversarial Networks (2019) — 92 citations
• Review the state-of-the-art technologies of semantic segmentation based on deep learning (2022) — 592 citations
• Proton Shuttles in CeO2/CeO2−δ Core–Shell Structure (2019) — 218 citations