Sungmin Lee

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 141 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 27 citations into it
• Artificial Intelligence — 16 citations into it

Whom Sungmin Lee trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Karen Simonyan
5. Alex Krizhevsky
6. Ross B. Girshick
7. Andrew Zisserman
8. Yoshua Bengio
9. Ilya Sutskever
10. Yann LeCun

Papers from Sungmin Lee's perspective

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

Their papers

• FickleNet: Weakly and Semi-Supervised Semantic Image Segmentation Using Stochastic Inference (2019) — 451 citations