Hong-Ming Yang

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 45 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it
• Artificial Intelligence — 10 citations into it
• Model Architectures — 7 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Hong-Ming Yang trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Yann LeCun
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Shaoqing Ren
7. Karen Simonyan
8. X. Zhang
9. Ross B. Girshick
10. Ilya Sutskever

Who trusts Hong-Ming Yang overall

1. Siyuan Shan
2. Sascha Saralajew
3. Pengfei Cao
4. Guangyao Chen
5. Haopeng Ren
6. Lu Yu
7. Yang Li
8. Lars Holdijk
9. Yubo Chen
10. Peixi Peng

Papers from Hong-Ming Yang's perspective

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

Their papers

• Robust Classification with Convolutional Prototype Learning (2018) — 464 citations