H. Kwon
Impact in
- Signal Processing top 10%
- Speech and Audio Processing
- Music and Audio Processing
- Biometric Identification and Security
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- Face recognition and analysis
- Face and Expression Recognition
Papers in
-
- Explainable Artificial Intelligence (XAI) 3
-
- Face recognition and analysis 4
- Video Surveillance and Tracking Methods 3
- Face and Expression Recognition 1
- Co-authors
- Nam Ik Cho (9 shared papers)Hyung Il Koo (8 shared papers)Nam Soo Kim (1 shared paper)Jong Won Shin (1 shared paper)Seok Hee Lee (3 shared papers)Sang Yoon Han (1 shared paper)Yoonsik Kim (1 shared paper)Jae Woong Soh (2 shared papers)
- Journals
- IEEE Access (2 papers)Journal of Nuclear Science and Technology (1 paper)Applied Physics Letters (1 paper)Cognitive Systems Research (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- South KoreaJapan
In The Last Decade
H. Kwon
15 papers receiving 198 citations
Peers
Comparison fields: 5 of 76
- Signal Processing 69
- Computer Vision and Pattern Recognition 63
- Human-Computer Interaction 13
- Computational Mathematics 1
- Computational Mechanics 32
Countries citing papers authored by H. Kwon
This map shows the geographic impact of H. Kwon'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 H. Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H. Kwon more than expected).
Fields of papers citing papers by H. Kwon
This network shows the impact of papers produced by H. Kwon. 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 H. Kwon. The network helps show where H. Kwon may publish in the future.
Co-authors
The 24 scholars most cited alongside H. Kwon, 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 | 2008 | 50 | |
| 2 | 2018 | 39 | |
| 3 | 2020 | 23 | |
| 4 | 2012 | 21 | |
| 5 | 2018 | 16 | |
| 6 | 2021 | 13 | |
| 7 | 2007 | 12 | |
| 8 | 2021 | 10 | |
| 9 | 2019 | 6 | |
| 10 | 2008 | 4 | |
| 11 | 2021 | 3 | |
| 12 | 2022 | 3 | |
| 13 | 2023 | 2 | |
| 14 | 2012 | 1 | |
| 15 | 2017 | 1 | |
| 16 | 2020 | 0 |
About H. Kwon
H. Kwon is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics, Materials Chemistry and Signal Processing, having authored 16 papers that have together received 204 indexed citations. Recurring topics across this work include Face recognition and analysis (4 papers), Cell Image Analysis Techniques (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Video Surveillance and Tracking Methods (3 papers), Machine Learning in Materials Science (2 papers), Gaze Tracking and Assistive Technology (1 paper), Advanced Adaptive Filtering Techniques (1 paper) and Face and Expression Recognition (1 paper). The work is most often cited by research in Signal Processing (69 citations), Computer Vision and Pattern Recognition (63 citations), Human-Computer Interaction (13 citations), Computational Mathematics (1 citation) and Computational Mechanics (32 citations). H. Kwon has collaborated with scholars based in South Korea and Japan. Frequent co-authors include Nam Ik Cho, Hyung Il Koo, Nam Soo Kim, Jong Won Shin, Seok Hee Lee, Sang Yoon Han, Yoonsik Kim, Jae Woong Soh, Jae‐Heon Kang and Nack‐Gyun Chung. Their work appears in journals such as IEEE Access, Journal of Nuclear Science and Technology, Applied Physics Letters, Cognitive Systems Research 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.