Geewook Kim

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 95 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 60 citations into it
• Artificial Intelligence — 50 citations into it
• Model Architectures — 26 citations into it
• Optimization & Training — 5 citations into it

Whom Geewook Kim trusts overall

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

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

Who trusts Geewook Kim overall

1. Charlotte Caucheteux

Papers from Geewook Kim's perspective

Ordered by how strongly the researchers Geewook Kim 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
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

• What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis (2019) — 570 citations
• OCR-Free Document Understanding Transformer (2021) — 538 citations
• Scale down Transformer by Grouping Features for a Lightweight Character-level Language Model (2020) — 3 citations