Ju-hong Lee

Artificial Intelligence · 2009

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 5 citations into it

Whom Ju-hong Lee trusts overall

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

1. Chin-Yew Lin
2. Hongyuan Zha
3. Yihong Gong
4. Xin Liu
5. Wei Xu
6. Julian Kupiec
7. Jan O. Pedersen

Who trusts Ju-hong Lee overall

1. Rasim M. Alguliyev
2. Michael Völske
3. Ramiz M. Aliguliyev
4. Martin Potthast

Papers from Ju-hong Lee's perspective

Ordered by how strongly the researchers Ju-hong Lee 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. Long Short-Term Memory
3. Document clustering based on non-negative matrix factorization
4. ImageNet classification with deep convolutional neural networks
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. ROUGE: A Package for Automatic Evaluation of Summaries
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Automatic generic document summarization based on non-negative matrix factorization (2009) — 163 citations