Seung Park
Impact in
- Health Informatics top 10%
-
- Advanced Image Processing Techniques
- Generative Adversarial Networks and Image Synthesis
- Digital Media Forensic Detection
Papers in
-
- Digital Media Forensic Detection 8
- Generative Adversarial Networks and Image Synthesis 8
- Advanced Image Processing Techniques 8
- Image Enhancement Techniques 6
- Co-authors
- Yong-Goo ShinSung-Jea KoLiron PantanowitzAnil V. ParwaniJames D. IversenHood ChathamSeung‐Wook KimJong-Il Yun
- Journals
- Applied Intelligence (3 papers)Journal of Pathology Informatics (3 papers)Scientific Reports (2 papers)IEEE Access (2 papers)IEEE Transactions on Neural Networks and Learning Systems (2 papers)
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Seung Park
69 papers receiving 695 citations
Peers
Comparison fields: 5 of 132
- Health Informatics 20
- Computer Vision and Pattern Recognition 186
- Computer Graphics and Computer-Aided Design 20
- Fluid Flow and Transfer Processes 31
- Ophthalmology 46
Countries citing papers authored by Seung Park
This map shows the geographic impact of Seung Park'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 Seung Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seung Park more than expected).
Fields of papers citing papers by Seung Park
This network shows the impact of papers produced by Seung Park. 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 Seung Park. The network helps show where Seung Park may publish in the future.
Co-authors
The 25 scholars most cited alongside Seung Park, 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 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 19 | |
| 6 | 2024 | 3 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 3 | |
| 9 | 2023 | 3 | |
| 10 | 2023 | 2 | |
| 11 | 2022 | 7 | |
| 12 | 2022 | 7 | |
| 13 | Unsupervised Deep Power Saving and Contrast Enhancement for OLED Displays. | 2019 | 3 |
| 14 | 2019 | 90 | |
| 15 | 2013 | 48 | |
| 16 | The Patient Specific QA of IMRT and VMAT Through the AAPM Task Group Report 119 | 2012 | 2 |
| 17 | 2012 | 45 | |
| 18 | 2012 | 8 | |
| 19 | A Study on the Multi-Criteria Decision Making for Effect Analysis and Decision Making of Weapon System | 2009 | 1 |
| 20 | 2009 | 2 |
About Seung Park
Seung Park is a scholar working on Health Informatics, Computer Vision and Pattern Recognition, Artificial Intelligence, Family Practice and Radiology, Nuclear Medicine and Imaging, having authored 74 papers that have together received 744 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (8 papers), Generative Adversarial Networks and Image Synthesis (8 papers), Advanced Image Processing Techniques (8 papers), Machine Learning in Healthcare (7 papers), AI in cancer detection (7 papers), Image Enhancement Techniques (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Color Science and Applications (5 papers). The work is most often cited by research in Health Informatics (20 citations), Computer Vision and Pattern Recognition (186 citations), Computer Graphics and Computer-Aided Design (20 citations), Fluid Flow and Transfer Processes (31 citations) and Ophthalmology (46 citations). Seung Park has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Yong-Goo Shin, Sung-Jea Ko, Liron Pantanowitz, Anil V. Parwani, James D. Iversen, Hood Chatham, Seung‐Wook Kim, Jong-Il Yun, Joel M. Bowman and Matthew G. Field. Their work appears in journals such as Applied Intelligence, Journal of Pathology Informatics, Scientific Reports, IEEE Access and IEEE Transactions on Neural Networks and Learning Systems.
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.