Jun-Mo Kim
Impact in
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- Medical Image Segmentation Techniques
- Image and Object Detection Techniques
- Image Retrieval and Classification Techniques
- Image and Signal Denoising Methods
- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
- Media Technology top 10%
Papers in
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- EEG and Brain-Computer Interfaces 11
- Neural dynamics and brain function 2
- Functional Brain Connectivity Studies 2
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- Neuroscience and Neural Engineering 3
- Co-authors
- John W. Fisher (2 shared papers)Müjdat Çetin (1 shared paper)Anthony Yezzi (1 shared paper)A. S. Willsky (1 shared paper)Tae‐Eui Kam (9 shared papers)William M. Wells (1 shared paper)Andy Tsai (1 shared paper)Alan S. Willsky (1 shared paper)
- Journals
- Expert Systems with Applications (2 papers)IEEE Journal of Biomedical and Health Informatics (1 paper)Frontiers in Human Neuroscience (1 paper)Sensors (1 paper)Digital Health (1 paper)
- Partner nations
- South KoreaUnited StatesTürkiye
In The Last Decade
Jun-Mo Kim
14 papers receiving 334 citations
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 219
- Media Technology 34
- Cognitive Neuroscience 61
- Biophysics 17
- Signal Processing 20
Countries citing papers authored by Jun-Mo Kim
This map shows the geographic impact of Jun-Mo Kim'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 Jun-Mo Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun-Mo Kim more than expected).
Fields of papers citing papers by Jun-Mo Kim
This network shows the impact of papers produced by Jun-Mo Kim. 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 Jun-Mo Kim. The network helps show where Jun-Mo Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun-Mo Kim, 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 | 2005 | 235 | |
| 2 | 2000 | 21 | |
| 3 | 2024 | 15 | |
| 4 | 2023 | 15 | |
| 5 | 2021 | 14 | |
| 6 | 2023 | 12 | |
| 7 | 2024 | 11 | |
| 8 | 2024 | 6 | |
| 9 | 2024 | 5 | |
| 10 | 2023 | 4 | |
| 11 | Comparison of the Results between Heidelberg Retina Tomography II and Stratus Optical Coherence Tomography in Glaucoma | 2006 | 3 |
| 12 | 2024 | 2 | |
| 13 | 2025 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2024 | 0 | |
| 17 | 2022 | 0 | |
| 18 | 2025 | 0 |
About Jun-Mo Kim
Jun-Mo Kim is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 18 papers that have together received 345 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (11 papers), Neuroscience and Neural Engineering (3 papers), Advanced Memory and Neural Computing (3 papers), ECG Monitoring and Analysis (3 papers), Neural dynamics and brain function (2 papers), Neural Networks and Applications (2 papers), Advanced MRI Techniques and Applications (2 papers) and Functional Brain Connectivity Studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (219 citations), Media Technology (34 citations), Cognitive Neuroscience (61 citations), Biophysics (17 citations) and Signal Processing (20 citations). Jun-Mo Kim has collaborated with scholars based in South Korea, United States and Türkiye. Frequent co-authors include John W. Fisher, Müjdat Çetin, Anthony Yezzi, A. S. Willsky, Tae‐Eui Kam, William M. Wells, Andy Tsai, Alan S. Willsky, Dong-Ok Won and Cheolsoo Park. Their work appears in journals such as Expert Systems with Applications, IEEE Journal of Biomedical and Health Informatics, Frontiers in Human Neuroscience, Sensors and Digital Health.
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.