Young-Chul Yoon
Impact in
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- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
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- Fire Detection and Safety Systems
Papers in
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- Video Surveillance and Tracking Methods 8
- Human Pose and Action Recognition 4
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- Infrared Target Detection Methodologies 4
- Co-authors
- Moongu Jeon (7 shared papers)Kwangjin Yoon (7 shared papers)Young-Min Song (5 shared papers)Du Yong Kim (2 shared papers)JiHyeon Song (1 shared paper)Tae Sung Hwang (1 shared paper)Young Do Koo (1 shared paper)Jeonghwan Gwak (1 shared paper)
- Journals
- IEEE Access (3 papers)Sensors (1 paper)Information Sciences (1 paper)2021 21st International Conference on Control, Automation and Systems (ICCAS) (1 paper)
- Partner nations
- South KoreaAustraliaCanada
In The Last Decade
Young-Chul Yoon
10 papers receiving 225 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 155
- Safety, Risk, Reliability and Quality 39
- Signal Processing 43
- Computer Networks and Communications 55
- Artificial Intelligence 77
Countries citing papers authored by Young-Chul Yoon
This map shows the geographic impact of Young-Chul Yoon'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 Young-Chul Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young-Chul Yoon more than expected).
Fields of papers citing papers by Young-Chul Yoon
This network shows the impact of papers produced by Young-Chul Yoon. 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 Young-Chul Yoon. The network helps show where Young-Chul Yoon may publish in the future.
Co-authors
The 10 scholars most cited alongside Young-Chul Yoon, 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 | 2018 | 54 | |
| 2 | 2020 | 47 | |
| 3 | 2019 | 45 | |
| 4 | 2019 | 26 | |
| 5 | 2020 | 26 | |
| 6 | 2018 | 17 | |
| 7 | 2022 | 7 | |
| 8 | 2021 | 3 | |
| 9 | 2018 | 3 | |
| 10 | Animal Detection in Huge Air-view Images using CNN-based Sliding Window | 2018 | 2 |
About Young-Chul Yoon
Young-Chul Yoon is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Artificial Intelligence, Global and Planetary Change and Biomedical Engineering, having authored 10 papers that have together received 230 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (8 papers), Infrared Target Detection Methodologies (4 papers), Human Pose and Action Recognition (4 papers), Advanced Chemical Sensor Technologies (2 papers), Impact of Light on Environment and Health (2 papers), Hand Gesture Recognition Systems (1 paper), Fire Detection and Safety Systems (1 paper) and Internet Traffic Analysis and Secure E-voting (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (155 citations), Safety, Risk, Reliability and Quality (39 citations), Signal Processing (43 citations), Computer Networks and Communications (55 citations) and Artificial Intelligence (77 citations). Young-Chul Yoon has collaborated with scholars based in South Korea, Australia and Canada. Frequent co-authors include Moongu Jeon, Kwangjin Yoon, Young-Min Song, Du Yong Kim, JiHyeon Song, Tae Sung Hwang, Young Do Koo, Jeonghwan Gwak, Kin‐Choong Yow and Kuk‐Jin Yoon. Their work appears in journals such as IEEE Access, Sensors, Information Sciences and 2021 21st International Conference on Control, Automation and Systems (ICCAS).
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.