Peng Su

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 2 papers; trusts 288 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 79 citations into it
• Artificial Intelligence — 65 citations into it
• Representation & Self-Supervised Learning — 33 citations into it
• Optimization & Training — 6 citations into it

Whom Peng Su trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Yoshua Bengio
7. Shaoqing Ren
8. Diederik P. Kingma
9. Ilya Sutskever
10. Christian Szegedy

Who trusts Peng Su overall

1. Shixiang Tang
2. Jinhong Deng
3. Shiqi Yang
4. Yu-Jhe Li

Papers from Peng Su's perspective

Ordered by how strongly the researchers Peng Su 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Adapting Object Detectors with Conditional Domain Normalization (2020) — 100 citations
• Gradient Regularized Contrastive Learning for Continual Domain Adaptation (2020) — 72 citations