Cheng Wu

Computer Vision and Pattern Recognition · with Huang · 2014–2019

A researcher in the Science corpus: 2 papers; trusts 48 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 45 citations into it; #14,670 of 21,575 by trust here, #14,151 by citations
• Artificial Intelligence — 37 citations into it; #23,726 of 35,345 by trust here, #21,316 by citations
• Representation & Self-Supervised Learning — 12 citations into it
• Optimization & Training — 10 citations into it

Whom Cheng Wu trusts overall

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

1. Alex Krizhevsky
2. Mikhail Belkin
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Kaiming He
6. Vladimir Naumovich Vapni
7. Karen Simonyan
8. G. Huang
9. Ilya Sutskever
10. Andrew Y. Ng

Who trusts Cheng Wu overall

1. G. Huang

Papers from Cheng Wu's perspective

Ordered by how strongly the researchers Cheng 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. Learning Multiple Layers of Features from Tiny Images
4. Gradient-based learning applied to document recognition
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Dropout: a simple way to prevent neural networks from overfitting

Their papers

• Implicit Semantic Data Augmentation for Deep Networks (2019) — 242 citations
• Semi-Supervised and Unsupervised Extreme Learning Machines (2014) — 741 citations