Min Beom Lee
Impact in
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- Digital Imaging for Blood Diseases
- Face recognition and analysis
- Signal Processing top 10%
- Biometric Identification and Security
Papers in
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- Face recognition and analysis 5
- Digital Imaging for Blood Diseases 2
- Advanced Neural Network Applications 2
- Digital Media Forensic Detection 2
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- Biometric Identification and Security 4
- Co-authors
- Kang Ryoung Park (10 shared papers)Muhammad Arsalan (4 shared papers)Muhammad Owais (3 shared papers)Tahir Mahmood (1 shared paper)Yu Hwan Kim (2 shared papers)Dong Seop Kim (1 shared paper)Adnan Haider (1 shared paper)Tuyen Danh Pham (2 shared papers)
- Journals
- IEEE Access (4 papers)Sensors (2 papers)Expert Systems with Applications (2 papers)Multimedia Tools and Applications (1 paper)Journal of Clinical Medicine (1 paper)
- Partner nations
- South Korea
In The Last Decade
Min Beom Lee
11 papers receiving 363 citations
Peers
Comparison fields: 5 of 89
- Computer Vision and Pattern Recognition 175
- Signal Processing 85
- Radiology, Nuclear Medicine and Imaging 153
- Health Informatics 7
- Artificial Intelligence 146
Countries citing papers authored by Min Beom Lee
This map shows the geographic impact of Min Beom 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 Min Beom Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min Beom Lee more than expected).
Fields of papers citing papers by Min Beom Lee
This network shows the impact of papers produced by Min Beom 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 Min Beom Lee. The network helps show where Min Beom Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Min Beom 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 | 2020 | 139 | |
| 2 | 2019 | 67 | |
| 3 | 2019 | 49 | |
| 4 | 2022 | 48 | |
| 5 | 2020 | 25 | |
| 6 | 2016 | 15 | |
| 7 | 2021 | 12 | |
| 8 | 2019 | 10 | |
| 9 | 2021 | 6 | |
| 10 | 2019 | 4 | |
| 11 | 2017 | 1 |
About Min Beom Lee
Min Beom Lee is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Ophthalmology, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 11 papers that have together received 376 indexed citations. Recurring topics across this work include Face recognition and analysis (5 papers), Biometric Identification and Security (4 papers), Digital Imaging for Blood Diseases (2 papers), Glaucoma and retinal disorders (2 papers), AI in cancer detection (2 papers), Advanced Neural Network Applications (2 papers), Digital Media Forensic Detection (2 papers) and Gaze Tracking and Assistive Technology (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (175 citations), Signal Processing (85 citations), Radiology, Nuclear Medicine and Imaging (153 citations), Health Informatics (7 citations) and Artificial Intelligence (146 citations). Min Beom Lee has collaborated with scholars based in South Korea. Frequent co-authors include Kang Ryoung Park, Muhammad Arsalan, Muhammad Owais, Tahir Mahmood, Yu Hwan Kim, Dong Seop Kim, Tahir Mahmood, Adnan Haider, Tuyen Danh Pham and Dat Tien Nguyen. Their work appears in journals such as IEEE Access, Sensors, Expert Systems with Applications, Multimedia Tools and Applications and Journal of Clinical Medicine.
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.