Seungho Lee

Computer Vision and Pattern Recognition · with Lee · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 299 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it
• Artificial Intelligence — 20 citations into it
• Model Architectures — 5 citations into it

Whom Seungho 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. Liang-Chieh Chen
6. Karen Simonyan
7. Yoshua Bengio
8. Yann LeCun
9. Diederik P. Kingma
10. Jia Deng

Who trusts Seungho Lee overall

1. Fabio Cermelli
2. Dina Bashkirova
3. Dario Fontanel

Papers from Seungho Lee's perspective

Ordered by how strongly the researchers Seungho 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. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
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
• Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation (2019) — 47 citations