Cheng-Yao Hong

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 44 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it
• Artificial Intelligence — 31 citations into it
• Representation & Self-Supervised Learning — 31 citations into it

Whom Cheng-Yao Hong trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Yann LeCun
6. Alec Radford
7. Ross B. Girshick
8. Diederik P. Kingma
9. Jia Deng
10. Ilya Sutskever

Papers from Cheng-Yao Hong's perspective

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

Their papers

• Decoupled Contrastive Learning (2021) — 259 citations