Seyoung Yun

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 129 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 26 citations into it
• Representation & Self-Supervised Learning — 23 citations into it
• Artificial Intelligence — 22 citations into it

Whom Seyoung Yun trusts overall

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

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

Papers from Seyoung Yun's perspective

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

Their papers

• MixCo: Mix-up Contrastive Learning for Visual Representation (2020) — 95 citations