Sang-Woo Lee
Impact in
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- Art History and Market Analysis
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- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Advanced Neural Network Applications
Papers in
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- Topic Modeling 8
- Natural Language Processing Techniques 5
- Domain Adaptation and Few-Shot Learning 4
- Speech and dialogue systems 2
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- Multimodal Machine Learning Applications 6
- Human Pose and Action Recognition 2
- Co-authors
- Jung-Woo Ha (5 shared papers)Byoung‐Tak Zhang (3 shared papers)Jin-Hwa Kim (1 shared paper)Jae-Hyun Jun (1 shared paper)David Waterman (2 shared papers)Minsuk Chang (1 shared paper)Sungdong Kim (1 shared paper)Dong‐Geol Choi (3 shared papers)
- Journals
- IEEE Robotics and Automation Letters (1 paper)Electronics (1 paper)Neural Networks (1 paper)Journal of Media Economics (2 papers)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Sang-Woo Lee
17 papers receiving 205 citations
Peers
Comparison fields: 5 of 58
- Visual Arts and Performing Arts 23
- Computer Vision and Pattern Recognition 97
- Artificial Intelligence 149
- Urban Studies 22
- Computational Mathematics 1
Countries citing papers authored by Sang-Woo Lee
This map shows the geographic impact of Sang-Woo Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sang-Woo Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sang-Woo Lee more than expected).
Fields of papers citing papers by Sang-Woo Lee
This network shows the impact of papers produced by Sang-Woo Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sang-Woo Lee. The network helps show where Sang-Woo Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Sang-Woo Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 120 | |
| 2 | 2002 | 21 | |
| 3 | 2007 | 18 | |
| 4 | 2021 | 12 | |
| 5 | 2021 | 11 | |
| 6 | 2023 | 7 | |
| 7 | 2017 | 6 | |
| 8 | Answerer in Questioner's Mind for Goal-Oriented Visual Dialogue. | 2018 | 4 |
| 9 | 2021 | 4 | |
| 10 | 2021 | 3 | |
| 11 | 2002 | 3 | |
| 12 | 2022 | 3 | |
| 13 | 2021 | 2 | |
| 14 | 2018 | 2 | |
| 15 | 2023 | 1 | |
| 16 | National Wind Atlas Database and Visualization Based on IDL | 2009 | 1 |
| 17 | 2023 | 1 | |
| 18 | 2020 | 0 |
About Sang-Woo Lee
Sang-Woo Lee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Urban Studies, Information Systems and Visual Arts and Performing Arts, having authored 18 papers that have together received 219 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Multimodal Machine Learning Applications (6 papers), Natural Language Processing Techniques (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Art History and Market Analysis (3 papers), Cultural Industries and Urban Development (3 papers), Human Pose and Action Recognition (2 papers) and Speech and dialogue systems (2 papers). The work is most often cited by research in Visual Arts and Performing Arts (23 citations), Computer Vision and Pattern Recognition (97 citations), Artificial Intelligence (149 citations), Urban Studies (22 citations) and Computational Mathematics (1 citation). Sang-Woo Lee has collaborated with scholars based in South Korea and United States. Frequent co-authors include Jung-Woo Ha, Byoung‐Tak Zhang, Jin-Hwa Kim, Jae-Hyun Jun, David Waterman, Minsuk Chang, Sungdong Kim, Dong‐Geol Choi, Jongchan Park and Kang Min Yoo. Their work appears in journals such as IEEE Robotics and Automation Letters, Electronics, Neural Networks, Journal of Media Economics and Findings of the Association for Computational Linguistics: ACL 2022.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.