Tae Sung Yoon
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Control and Systems Engineering top 10%
- Aerospace Engineering
- Artificial Intelligence
- Topics
- Electrical Fault Detection and Protection (12 papers)Target Tracking and Data Fusion in Sensor Networks (11 papers)Indoor and Outdoor Localization Technologies (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
- Partner nations
- South KoreaJapanUnited States
In The Last Decade
Tae Sung Yoon
41 papers receiving 292 citations
Peers
Comparison fields: 5 of 62
- Electrical and Electronic Engineering 117
- Computer Vision and Pattern Recognition 77
- Control and Systems Engineering 76
- Aerospace Engineering 66
- Artificial Intelligence 52
Countries citing papers authored by Tae Sung Yoon
This map shows the geographic impact of Tae Sung 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 Tae Sung Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tae Sung Yoon more than expected).
Fields of papers citing papers by Tae Sung Yoon
This network shows the impact of papers produced by Tae Sung 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 Tae Sung Yoon. The network helps show where Tae Sung Yoon may publish in the future.
Co-authorship network of co-authors of Tae Sung Yoon
This figure shows the co-authorship network connecting the top 25 collaborators of Tae Sung Yoon. A scholar is included among the top collaborators of Tae Sung 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 Tae Sung Yoon. Tae Sung 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 | 27 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | Position and heading tracking in sensor network via instrumental variable estimation | 1 |
| 8 | 0 | |
| 9 | 1 | |
| 10 | Robust state estimation approach to target localization using range difference of arrival data | 6 |
| 11 | 6 | |
| 12 | Multiple Fault Detection on a Coaxial Cable via TFDR | 0 |
| 13 | 2 | |
| 14 | 11 | |
| 15 | Robust extended kalman filtering via krein space estimation | 1 |
| 16 | 23 | |
| 17 | 0 | |
| 18 | 4 | |
| 19 | 20 | |
| 20 | Korean Vowel Recognition in Noise Using the Auditory Model | 5 |
About Tae Sung Yoon
Tae Sung Yoon is a scholar working on Control and Systems Engineering, Electrical and Electronic Engineering and Artificial Intelligence, having authored 49 papers that have together received 321 indexed citations. Recurring topics across this work include Electrical Fault Detection and Protection (12 papers), Target Tracking and Data Fusion in Sensor Networks (11 papers) and Indoor and Outdoor Localization Technologies (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (77 citations), Control and Systems Engineering (76 citations) and Signal Processing (33 citations). Tae Sung Yoon has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Jin Bae Park, Jongmin Jeong, Jin Bae Park, Won‐Sang Ra, Euntai Kim, Jongwon Lee, Dong Joon Kim, S.H. Park, J.B. Park and Jin Park. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.