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
- Functional Brain Connectivity Studies 2
- Neural dynamics and brain function 1
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- Neuroscience and Neural Engineering 4
- Co-authors
- A. S. WillskyJohn W. FisherAnthony YezziMüjdat ÇetinTae‐Eui KamDong-Ok WonKo Keun KimCheolsoo Park
- Journals
- Expert Systems with Applications (2 papers)IEEE Transactions on Image Processing (1 paper)Frontiers in Human Neuroscience (1 paper)Sensors (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Jun-Mo Kim
12 papers receiving 268 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 180
- Media Technology 29
- Biophysics 16
- Cognitive Neuroscience 45
- Computational Mathematics 1
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-authorship network
The 23 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 14 | |
| 6 | 2024 | 9 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 2 | |
| 10 | 2023 | 11 | |
| 11 | 2023 | 0 | |
| 12 | 2023 | 8 | |
| 13 | 2023 | 4 | |
| 14 | 2021 | 14 | |
| 15 | Comparison of the Results between Heidelberg Retina Tomography II and Stratus Optical Coherence Tomography in Glaucoma | 2006 | 3 |
| 16 | 2005 | 205 |
About Jun-Mo Kim
Jun-Mo Kim is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Human-Computer Interaction, Cardiology and Cardiovascular Medicine and Neurology, having authored 16 papers that have together received 277 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (11 papers), Neuroscience and Neural Engineering (4 papers), ECG Monitoring and Analysis (3 papers), Advanced Memory and Neural Computing (3 papers), Neural Networks and Applications (2 papers), Functional Brain Connectivity Studies (2 papers), Action Observation and Synchronization (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (180 citations), Media Technology (29 citations), Biophysics (16 citations), Cognitive Neuroscience (45 citations) and Computational Mathematics (1 citation). Jun-Mo Kim has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include A. S. Willsky, John W. Fisher, Anthony Yezzi, Müjdat Çetin, Tae‐Eui Kam, Dong-Ok Won, Ko Keun Kim, Cheolsoo Park, Jong‐Suk Kim and Ji-Hoon Jeong. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Image Processing, Frontiers in Human Neuroscience, Sensors and IEEE Journal of Biomedical and Health Informatics.
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.