Seungmin Lee
Artificial Intelligence · 2020
A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 24 citations into it
- Optimization & Training — 20 citations into it
- Computer Vision and Pattern Recognition — 18 citations into it
Whom Seungmin Lee trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Seungmin Lee's perspective
Ordered by how strongly the researchers Seungmin Lee trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Large Scale Distributed Deep Networks
- Learning Multiple Layers of Features from Tiny Images