Sanghoon Jun
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Water Systems and Optimization 9
- Infrastructure Maintenance and Monitoring 3
- Geotechnical Engineering and Underground Structures 3
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- Music Technology and Sound Studies 7
- Co-authors
- Joon Beom Seo (4 shared papers)Namkug Kim (4 shared papers)Guk Bae Kim (2 shared papers)Hyunna Lee (1 shared paper)June‐Goo Lee (1 shared paper)Eenjun Hwang (13 shared papers)Seungmin Rho (8 shared papers)Kevin Lansey (6 shared papers)
- Journals
- Journal of Water Resources Planning and Management (4 papers)Journal of Digital Imaging (3 papers)Multimedia Tools and Applications (3 papers)Water Research X (2 papers)Water Resources Management (2 papers)
- Partner nations
- South KoreaUnited StatesTürkiye
In The Last Decade
Sanghoon Jun
25 papers receiving 1.2k citations
Sanghoon Jun's Hit Papers
Peers
Comparison fields: 5 of 136
- Health Informatics 104
- Radiology, Nuclear Medicine and Imaging 487
- Signal Processing 122
- Artificial Intelligence 354
- Computer Vision and Pattern Recognition 201
Countries citing papers authored by Sanghoon Jun
This map shows the geographic impact of Sanghoon Jun'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 Sanghoon Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanghoon Jun more than expected).
Fields of papers citing papers by Sanghoon Jun
This network shows the impact of papers produced by Sanghoon Jun. 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 Sanghoon Jun. The network helps show where Sanghoon Jun may publish in the future.
Co-authors
The 22 scholars most cited alongside Sanghoon Jun, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep Learning in Medical Imaging: General Overview Hit paper breakdown → | 2017 | 848 |
| 2 | 2009 | 95 | |
| 3 | 2017 | 81 | |
| 4 | 2017 | 56 | |
| 5 | 2008 | 25 | |
| 6 | 2021 | 15 | |
| 7 | 2017 | 14 | |
| 8 | 2015 | 12 | |
| 9 | 2023 | 11 | |
| 10 | 2010 | 10 | |
| 11 | 2023 | 8 | |
| 12 | 2022 | 8 | |
| 13 | 2021 | 7 | |
| 14 | 2014 | 6 | |
| 15 | 2013 | 6 | |
| 16 | 2017 | 5 | |
| 17 | 2016 | 5 | |
| 18 | 2025 | 4 | |
| 19 | 2009 | 4 | |
| 20 | 2013 | 4 |
About Sanghoon Jun
Sanghoon Jun is a scholar working on Civil and Structural Engineering, Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 27 papers that have together received 1.2k indexed citations. Recurring topics across this work include Water Systems and Optimization (9 papers), Music and Audio Processing (9 papers), Music Technology and Sound Studies (7 papers), Speech and Audio Processing (5 papers), COVID-19 diagnosis using AI (3 papers), Water Quality Monitoring Technologies (3 papers), Infrastructure Maintenance and Monitoring (3 papers) and Geotechnical Engineering and Underground Structures (3 papers). The work is most often cited by research in Health Informatics (104 citations), Radiology, Nuclear Medicine and Imaging (487 citations), Signal Processing (122 citations), Artificial Intelligence (354 citations) and Computer Vision and Pattern Recognition (201 citations). Sanghoon Jun has collaborated with scholars based in South Korea, United States and Türkiye. Frequent co-authors include Joon Beom Seo, Namkug Kim, Guk Bae Kim, Hyunna Lee, June‐Goo Lee, Eenjun Hwang, Seungmin Rho, Kevin Lansey, Jihoon Moon and David A. Lynch. Their work appears in journals such as Journal of Water Resources Planning and Management, Journal of Digital Imaging, Multimedia Tools and Applications, Water Research X and Water Resources Management.
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.