Taehun Kim

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 88 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 25 citations into it
• Artificial Intelligence — 10 citations into it
• Oncology — 8 citations into it
• Model Architectures — 5 citations into it

Whom Taehun Kim trusts overall

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

1. Diederik P. Kingma
2. John F. Canny
3. Kaiming He
4. Ross B. Girshick
5. Geoffrey E. Hinton
6. Debesh Jha
7. Tsung-Yi Lin
8. Alex Krizhevsky
9. Jimmy Ba
10. Jorge Bernal

Papers from Taehun Kim's perspective

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

Their papers

• UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation (2021) — 367 citations