Nam Ik Cho

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 117 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 32 citations into it
• Media Technology — 23 citations into it
• Artificial Intelligence — 11 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Meta & Continual Learning — 5 citations into it

Whom Nam Ik Cho trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Oriol Vinyals
5. Jimmy Ba
6. Kaiming He
7. Yoshua Bengio
8. Yann LeCun
9. Ilya Sutskever
10. Tomer Michaeli

Papers from Nam Ik Cho's perspective

Ordered by how strongly the researchers Nam Ik Cho 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
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. Learning Multiple Layers of Features from Tiny Images

Their papers

• Meta-Transfer Learning for Zero-Shot Super-Resolution (2020) — 320 citations