Minhyun Lee

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 270 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 36 citations into it
• Artificial Intelligence — 18 citations into it

Whom Minhyun Lee trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Jia Deng
6. Yann LeCun
7. Karen Simonyan
8. Diederik P. Kingma
9. Yoshua Bengio
10. Liang-Chieh Chen

Papers from Minhyun Lee's perspective

Ordered by how strongly the researchers Minhyun Lee 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Going deeper with convolutions

Their papers

• Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation (2021) — 276 citations
• Determining the Peer-to-Peer electricity trading price and strategy for energy prosumers and consumers within a microgrid (2020) — 120 citations