Seung-Min Mun
Impact in
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- Digital Media Forensic Detection
- Advanced Steganography and Watermarking Techniques
- Generative Adversarial Networks and Image Synthesis
- Chaos-based Image/Signal Encryption
- Advanced Image Processing Techniques
- Advanced Image and Video Retrieval Techniques
- Media Technology top 10%
- Image Processing Techniques and Applications
Papers in
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- Digital Media Forensic Detection 8
- Advanced Steganography and Watermarking Techniques 5
- Generative Adversarial Networks and Image Synthesis 2
- Image and Video Stabilization 2
- Advanced Image Processing Techniques 2
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- Adversarial Robustness in Machine Learning 1
- Co-authors
- Heung-Kyu Lee (8 shared papers)Haneol Jang (5 shared papers)Dongkyu Kim (5 shared papers)Seung-Hun Nam (4 shared papers)Sunghee Choi (4 shared papers)Jong‐Uk Hou (2 shared papers)In-Jae Yu (2 shared papers)Jinseok Park (1 shared paper)
- Journals
- IEEE Signal Processing Letters (2 papers)Multimedia Tools and Applications (1 paper)IEEE Access (1 paper)Sensors (1 paper)Neurocomputing (1 paper)
- Partner nations
- South Korea
In The Last Decade
Seung-Min Mun
11 papers receiving 277 citations
Peers
Comparison fields: 5 of 33
- Computer Vision and Pattern Recognition 273
- Media Technology 42
- Signal Processing 49
- Computer Graphics and Computer-Aided Design 14
- Biophysics 10
Countries citing papers authored by Seung-Min Mun
This map shows the geographic impact of Seung-Min Mun'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-Min Mun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seung-Min Mun more than expected).
Fields of papers citing papers by Seung-Min Mun
This network shows the impact of papers produced by Seung-Min Mun. 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-Min Mun. The network helps show where Seung-Min Mun may publish in the future.
Co-authors
The 9 scholars most cited alongside Seung-Min Mun, 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 | 2019 | 115 | |
| 2 | 2017 | 54 | |
| 3 | 2017 | 33 | |
| 4 | 2017 | 26 | |
| 5 | 2017 | 22 | |
| 6 | 2020 | 14 | |
| 7 | 2019 | 13 | |
| 8 | 2015 | 9 | |
| 9 | 2020 | 8 | |
| 10 | A Study on Damage Detection of Cutting Tool Using Neural Network and Cutting Force Signal | 1997 | 2 |
| 11 | 2015 | 1 | |
| 12 | 2016 | 1 |
About Seung-Min Mun
Seung-Min Mun is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Electrical and Electronic Engineering and Organic Chemistry, having authored 12 papers that have together received 298 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (8 papers), Advanced Steganography and Watermarking Techniques (5 papers), Antenna Design and Analysis (2 papers), Microwave Engineering and Waveguides (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Image and Video Stabilization (2 papers), Advanced Image Processing Techniques (2 papers) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (273 citations), Media Technology (42 citations), Signal Processing (49 citations), Computer Graphics and Computer-Aided Design (14 citations) and Biophysics (10 citations). Seung-Min Mun has collaborated with scholars based in South Korea. Frequent co-authors include Heung-Kyu Lee, Haneol Jang, Dongkyu Kim, Seung-Hun Nam, Sunghee Choi, Jong‐Uk Hou, In-Jae Yu, Jinseok Park and Dongkyu Kim. Their work appears in journals such as IEEE Signal Processing Letters, Multimedia Tools and Applications, IEEE Access, Sensors and Neurocomputing.
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.