Ju Hong Yoon
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Aerospace Engineering top 10%
- Automotive Engineering
- Electrical and Electronic Engineering
- Co-authors
- Kuk‐Jin YoonMing–Hsuan YangJongwoo LimDu Yong KimVladimir ShinKuk-Jin YoonYong‐Hoon KimMoongu Jeon
- Topics
- Video Surveillance and Tracking Methods (8 papers)Target Tracking and Data Fusion in Sensor Networks (6 papers)Human Pose and Action Recognition (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Signal ProcessingInternational Journal of Computer Vision
- Partner nations
- South KoreaUnited StatesAustralia
In The Last Decade
Ju Hong Yoon
14 papers receiving 382 citations
Peers
Comparison fields: 5 of 47
- Computer Vision and Pattern Recognition 304
- Artificial Intelligence 149
- Aerospace Engineering 102
- Automotive Engineering 50
- Electrical and Electronic Engineering 39
Countries citing papers authored by Ju Hong Yoon
This map shows the geographic impact of Ju Hong 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 Ju Hong Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ju Hong Yoon more than expected).
Fields of papers citing papers by Ju Hong Yoon
This network shows the impact of papers produced by Ju Hong 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 Ju Hong Yoon. The network helps show where Ju Hong Yoon may publish in the future.
Co-authorship network of co-authors of Ju Hong Yoon
This figure shows the co-authorship network connecting the top 25 collaborators of Ju Hong Yoon. A scholar is included among the top collaborators of Ju Hong 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 Ju Hong Yoon. Ju Hong 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 | 25 | |
| 2 | 1 | |
| 3 | 122 | |
| 4 | 142 | |
| 5 | 21 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 20 | |
| 11 | 8 | |
| 12 | 38 | |
| 13 | 6 | |
| 14 | 6 |
About Ju Hong Yoon
Ju Hong Yoon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, having authored 14 papers that have together received 400 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (8 papers), Target Tracking and Data Fusion in Sensor Networks (6 papers) and Human Pose and Action Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (304 citations), Artificial Intelligence (149 citations) and Automotive Engineering (50 citations). Ju Hong Yoon has collaborated with scholars based in South Korea, United States and Australia. Frequent co-authors include Kuk‐Jin Yoon, Ming–Hsuan Yang, Jongwoo Lim, Du Yong Kim, Vladimir Shin, Kuk-Jin Yoon, Yong‐Hoon Kim, Moongu Jeon, Seung‐Hwan Bae and Youngbae Hwang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Signal Processing and International Journal of Computer Vision.
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.