Sangeun Han

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 232 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 20 citations into it
• Artificial Intelligence — 13 citations into it

Whom Sangeun Han trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Andrew Zisserman
7. Liang-Chieh Chen
8. Ross B. Girshick
9. Yunchao Wei
10. Jia Deng

Papers from Sangeun Han's perspective

Ordered by how strongly the researchers Sangeun Han 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. ImageNet: A large-scale hierarchical image database
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation (2021) — 138 citations