Songkuk Kim

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 395 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 52 citations into it
• Artificial Intelligence — 48 citations into it
• Model Architectures — 24 citations into it
• Optimization & Training — 17 citations into it
• Scaling & Learning Theory — 5 citations into it

Whom Songkuk Kim trusts overall

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

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

Papers from Songkuk Kim's perspective

Ordered by how strongly the researchers Songkuk 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• How Do Vision Transformers Work? (2022) — 695 citations