Jae Shin Yoon
- Computer Vision and Pattern Recognition top 5%
- Aerospace Engineering top 10%
- Automotive Engineering top 10%
- Media Technology top 10%
- Computational Mechanics
- Co-authors
- In So KweonSoonmin HwangKibaek ParkYukyung ChoiKyounghwan AnNamil KimHyun Soo ParkJaesik Park
- Topics
- Video Surveillance and Tracking Methods (7 papers)Human Pose and Action Recognition (6 papers)Advanced Vision and Imaging (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceACM Transactions on GraphicsIEEE Transactions on Intelligent Transportation Systems
- Partner nations
- United StatesSouth KoreaIsrael
In The Last Decade
Jae Shin Yoon
14 papers receiving 401 citations
Peers
Comparison fields: 5 of 60
- Computer Vision and Pattern Recognition 330
- Aerospace Engineering 119
- Automotive Engineering 78
- Media Technology 47
- Computational Mechanics 44
Countries citing papers authored by Jae Shin Yoon
This map shows the geographic impact of Jae Shin 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 Jae Shin Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jae Shin Yoon more than expected).
Fields of papers citing papers by Jae Shin Yoon
This network shows the impact of papers produced by Jae Shin 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 Jae Shin Yoon. The network helps show where Jae Shin Yoon may publish in the future.
Co-authorship network of co-authors of Jae Shin Yoon
This figure shows the co-authorship network connecting the top 25 collaborators of Jae Shin Yoon. A scholar is included among the top collaborators of Jae Shin Yoon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jae Shin Yoon. Jae Shin Yoon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 7 | |
| 6 | 6 | |
| 7 | 7 | |
| 8 | 8 | |
| 9 | 58 | |
| 10 | 19 | |
| 11 | 246 | |
| 12 | HUMBI 1.0: HUman Multiview Behavioral Imaging Dataset. | 4 |
| 13 | 31 | |
| 14 | 12 | |
| 15 | 14 | |
| 16 | 5 |
About Jae Shin Yoon
Jae Shin Yoon is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics, having authored 16 papers that have together received 424 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (7 papers), Human Pose and Action Recognition (6 papers) and Advanced Vision and Imaging (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (330 citations), Automotive Engineering (78 citations) and Geology (34 citations). Jae Shin Yoon has collaborated with scholars based in United States, South Korea and Israel. Frequent co-authors include In So Kweon, Soonmin Hwang, Kibaek Park, Yukyung Choi, Kyounghwan An, Namil Kim, Hyun Soo Park, Jaesik Park, Jihun Yu and P. Venkatesh. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and IEEE Transactions on Intelligent Transportation 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.