Songfan Yang

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 669 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 103 citations into it; #6,159 of 21,575 by trust here, #10,334 by citations
• Artificial Intelligence — 28 citations into it; #8,904 of 35,345 by trust here, #16,166 by citations
• Media Technology — 27 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Model Architectures — 11 citations into it
• Computational Mechanics — 8 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Optimization & Training — 6 citations into it

Whom Songfan Yang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Ross B. Girshick
4. Kaiming He
5. Yann LeCun
6. Li Fei-Fei
7. Andrew Zisserman
8. Antonio Torralba
9. Ilya Sutskever
10. Yoshua Bengio

Who trusts Songfan Yang overall

1. Golnaz Ghiasi
2. Yu-Xiong Wang
3. Xilai Li
4. Charless C. Fowlkes
5. Chun-Fu Chen
6. Martial Hebert
7. Xi Song
8. Tianfu Wu
9. Deva Ramanan
10. Quanfu Fan

Papers from Songfan Yang's perspective

Ordered by how strongly the researchers Songfan 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. 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. 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

• Multi-scale Recognition with DAG-CNNs (2015) — 209 citations
• CLEARER: Multi-Scale Neural Architecture Search for Image Restoration (2020) — 88 citations
• Structured AutoEncoders for Subspace Clustering (2018) — 326 citations