Sung Kim

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 150 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 25 citations into it
• Generative Models — 18 citations into it
• Artificial Intelligence — 11 citations into it
• Signal Processing — 10 citations into it
• Speech & Audio — 5 citations into it

Whom Sung Kim trusts overall

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

1. Diederik P. Kingma
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Alex Krizhevsky
6. Andrew Zisserman
7. Alec Radford
8. Yann LeCun
9. Pascal Vincent
10. Kaiming He

Who trusts Sung Kim overall

1. Yunpeng Li
2. Marco Tagliasacchi

Papers from Sung Kim's perspective

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

Their papers

• Bandwidth Extension on Raw Audio via Generative Adversarial Networks (2019) — 33 citations