Suan Lee
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Face recognition and analysis
- Human Pose and Action Recognition
Papers in
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- Video Analysis and Summarization 4
- Face recognition and analysis 4
- Advanced Image and Video Retrieval Techniques 4
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- Text and Document Classification Technologies 3
- Co-authors
- Wookey Lee (19 shared papers)Jinho Kim (15 shared papers)Bong Sup Shim (1 shared paper)Buşra Özlü (1 shared paper)Minkyu Kim (4 shared papers)In‐Su Bae (1 shared paper)Nam‐Soo Kim (2 shared papers)Renee Lay Hong Lim (1 shared paper)
- Journals
- Electronics (4 papers)Applied Sciences (3 papers)Sensors (2 papers)Scientometrics (1 paper)Image and Vision Computing (1 paper)
- Partner nations
- South KoreaChinaMalaysia
In The Last Decade
Suan Lee
48 papers receiving 404 citations
Peers
Comparison fields: 5 of 118
- Computer Vision and Pattern Recognition 118
- Computational Mathematics 3
- Management of Technology and Innovation 33
- Signal Processing 50
- Human-Computer Interaction 25
Countries citing papers authored by Suan Lee
This map shows the geographic impact of Suan 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 Suan Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suan Lee more than expected).
Fields of papers citing papers by Suan Lee
This network shows the impact of papers produced by Suan 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 Suan Lee. The network helps show where Suan Lee may publish in the future.
Co-authors
The 18 scholars most cited alongside Suan 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
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 65 | |
| 2 | 2021 | 45 | |
| 3 | 2021 | 32 | |
| 4 | 2022 | 28 | |
| 5 | 2023 | 22 | |
| 6 | 2023 | 18 | |
| 7 | 2024 | 15 | |
| 8 | 2022 | 15 | |
| 9 | 2020 | 11 | |
| 10 | 2002 | 10 | |
| 11 | 2021 | 10 | |
| 12 | 2015 | 10 | |
| 13 | 2023 | 9 | |
| 14 | 2020 | 9 | |
| 15 | 2018 | 8 | |
| 16 | 2020 | 8 | |
| 17 | 2024 | 7 | |
| 18 | 2021 | 7 | |
| 19 | 2024 | 6 | |
| 20 | 2020 | 6 |
About Suan Lee
Suan Lee is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Signal Processing and Computer Networks and Communications, having authored 56 papers that have together received 423 indexed citations. Recurring topics across this work include Data Management and Algorithms (5 papers), Advanced Database Systems and Queries (5 papers), Machine Fault Diagnosis Techniques (4 papers), Video Analysis and Summarization (4 papers), Recommender Systems and Techniques (4 papers), Face recognition and analysis (4 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (118 citations), Computational Mathematics (3 citations), Management of Technology and Innovation (33 citations), Signal Processing (50 citations) and Human-Computer Interaction (25 citations). Suan Lee has collaborated with scholars based in South Korea, China and Malaysia. Frequent co-authors include Wookey Lee, Jinho Kim, Bong Sup Shim, Buşra Özlü, Minkyu Kim, In‐Su Bae, Nam‐Soo Kim, Renee Lay Hong Lim, Yang‐Sae Moon and Eun Yu. Their work appears in journals such as Electronics, Applied Sciences, Sensors, Scientometrics and Image and Vision Computing.
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.