Pyong-Kun Kim
Impact in
-
- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Video Analysis and Summarization
- Advanced Image and Video Retrieval Techniques
- Media Technology top 10%
- Vehicle License Plate Recognition
Papers in
-
- Video Surveillance and Tracking Methods 11
- Advanced Neural Network Applications 4
- Human Pose and Action Recognition 3
-
- Vehicle License Plate Recognition 4
- Co-authors
- Kwang‐Ju Kim (11 shared papers)Yun-Su Chung (4 shared papers)Doo-Hyun Choi (4 shared papers)Jenq–Neng Hwang (4 shared papers)Chung‐I Huang (3 shared papers)Jiacheng Sun (1 shared paper)Zhongyu Jiang (2 shared papers)You-Ze Cho (1 shared paper)
- Journals
- Electronics (1 paper)IEEE Access (1 paper)The Journal of Korean Institute of Communications and Information Sciences (1 paper)
- Partner nations
- South KoreaUnited StatesTaiwan
In The Last Decade
Pyong-Kun Kim
14 papers receiving 201 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 168
- Media Technology 48
- Automotive Engineering 33
- Building and Construction 23
- Industrial and Manufacturing Engineering 10
Countries citing papers authored by Pyong-Kun Kim
This map shows the geographic impact of Pyong-Kun 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 Pyong-Kun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pyong-Kun Kim more than expected).
Fields of papers citing papers by Pyong-Kun Kim
This network shows the impact of papers produced by Pyong-Kun 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 Pyong-Kun Kim. The network helps show where Pyong-Kun Kim may publish in the future.
Co-authors
The 12 scholars most cited alongside Pyong-Kun 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 | 2019 | 59 | |
| 2 | 2018 | 41 | |
| 3 | 2017 | 39 | |
| 4 | 2024 | 28 | |
| 5 | 2023 | 15 | |
| 6 | 2023 | 14 | |
| 7 | 2018 | 9 | |
| 8 | 2021 | 3 | |
| 9 | 2024 | 3 | |
| 10 | 2020 | 2 | |
| 11 | 2022 | 2 | |
| 12 | 2020 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2018 | 1 | |
| 15 | 2024 | 0 |
About Pyong-Kun Kim
Pyong-Kun Kim is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Building and Construction and Biomedical Engineering, having authored 15 papers that have together received 218 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (11 papers), Vehicle License Plate Recognition (4 papers), Advanced Neural Network Applications (4 papers), Human Pose and Action Recognition (3 papers), Traffic Prediction and Management Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Gait Recognition and Analysis (2 papers) and Web Data Mining and Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (168 citations), Media Technology (48 citations), Automotive Engineering (33 citations), Building and Construction (23 citations) and Industrial and Manufacturing Engineering (10 citations). Pyong-Kun Kim has collaborated with scholars based in South Korea, United States and Taiwan. Frequent co-authors include Kwang‐Ju Kim, Yun-Su Chung, Doo-Hyun Choi, Jenq–Neng Hwang, Chung‐I Huang, Jiacheng Sun, Zhongyu Jiang, You-Ze Cho, Soo In Lee and Haiqing Du. Their work appears in journals such as Electronics, IEEE Access and The Journal of Korean Institute of Communications and Information Sciences.
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.