Yeong Jun Koh
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Genetics
- Animal Science and Zoology
- Artificial Intelligence
- Co-authors
- Chang‐Su KimChulwoo LeeSeung Hwan LeeJun Heon LeeYoungbae KimYoung‐Kuk KimHanul KimWon-Dong Jang
- Topics
- Advanced Vision and Imaging (11 papers)Video Surveillance and Tracking Methods (9 papers)Visual Attention and Saliency Detection (8 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Partner nations
- South KoreaJapanUnited States
In The Last Decade
Yeong Jun Koh
29 papers receiving 397 citations
Peers
Comparison fields: 5 of 58
- Computer Vision and Pattern Recognition 315
- Media Technology 75
- Genetics 34
- Animal Science and Zoology 24
- Artificial Intelligence 20
Countries citing papers authored by Yeong Jun Koh
This map shows the geographic impact of Yeong Jun Koh'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 Yeong Jun Koh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yeong Jun Koh more than expected).
Fields of papers citing papers by Yeong Jun Koh
This network shows the impact of papers produced by Yeong Jun Koh. 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 Yeong Jun Koh. The network helps show where Yeong Jun Koh may publish in the future.
Co-authorship network of co-authors of Yeong Jun Koh
This figure shows the co-authorship network connecting the top 25 collaborators of Yeong Jun Koh. A scholar is included among the top collaborators of Yeong Jun Koh 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 Yeong Jun Koh. Yeong Jun Koh 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 | 6 | |
| 5 | 12 | |
| 6 | 0 | |
| 7 | 4 | |
| 8 | 7 | |
| 9 | 14 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 51 | |
| 13 | 2 | |
| 14 | Meta learning for unsupervised clustering | 2 |
| 15 | 10 | |
| 16 | 11 | |
| 17 | 2 | |
| 18 | 30 | |
| 19 | 37 | |
| 20 | 16 |
About Yeong Jun Koh
Yeong Jun Koh is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Animal Science and Zoology, having authored 35 papers that have together received 408 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Video Surveillance and Tracking Methods (9 papers) and Visual Attention and Saliency Detection (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (315 citations), Media Technology (75 citations) and Computer Graphics and Computer-Aided Design (13 citations). Yeong Jun Koh has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Chang‐Su Kim, Chulwoo Lee, Seung Hwan Lee, Jun Heon Lee, Youngbae Kim, Young‐Kuk Kim, Hanul Kim, Won-Dong Jang, Seong-Gyun Jeong and Kyung-Rae Kim. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Image Processing.
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.