Seonghyun Kim
- Computer Vision and Pattern Recognition top 10%
- Safety, Risk, Reliability and Quality top 5%
- Global and Planetary Change
- Computer Networks and Communications
- Aerospace Engineering
- Co-authors
- Yong-Tae LeeWon–Jae LeeMin Sung ChoiHyun‐Woo LeeHyun–Woo LeeDonghun LeeYoung-Sung SonMyung-Ki Cheoun
- Topics
- Reinforcement Learning in Robotics (5 papers)Fire Detection and Safety Systems (3 papers)Evolutionary Algorithms and Applications (3 papers)
- Cited by
- Safety, Risk, Reliability and QualityComputer Vision and Pattern RecognitionGlobal and Planetary Change
- Partner nations
- South KoreaUnited States
In The Last Decade
Seonghyun Kim
15 papers receiving 179 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 86
- Safety, Risk, Reliability and Quality 79
- Global and Planetary Change 57
- Computer Networks and Communications 29
- Aerospace Engineering 27
Countries citing papers authored by Seonghyun Kim
This map shows the geographic impact of Seonghyun Kim'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 Seonghyun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seonghyun Kim more than expected).
Fields of papers citing papers by Seonghyun Kim
This network shows the impact of papers produced by Seonghyun Kim. 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 Seonghyun Kim. The network helps show where Seonghyun Kim may publish in the future.
Co-authorship network of co-authors of Seonghyun Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Seonghyun Kim. A scholar is included among the top collaborators of Seonghyun Kim 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 Seonghyun Kim. Seonghyun Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 18 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 28 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 8 | |
| 14 | 72 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 7 | |
| 18 | 39 |
About Seonghyun Kim
Seonghyun Kim is a scholar working on Safety, Risk, Reliability and Quality, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 18 papers that have together received 186 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Fire Detection and Safety Systems (3 papers) and Evolutionary Algorithms and Applications (3 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (79 citations), Computer Vision and Pattern Recognition (86 citations) and Global and Planetary Change (57 citations). Seonghyun Kim has collaborated with scholars based in South Korea and United States. Frequent co-authors include Yong-Tae Lee, Won–Jae Lee, Min Sung Choi, Hyun‐Woo Lee, Hyun–Woo Lee, Donghun Lee, Young-Sung Son, Myung-Ki Cheoun, Eunja Ha and Myeong-Hwan Mun. Their work appears in journals such as Physics Letters B, IEEE Access and IEEE Transactions on Electron Devices.
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.