Sangwon Kim
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Co-authors
- Byoung Chul KoJae-Yeal NamChang-Hyun ParkZeeshan Haider JaffariChang‐Min KimJaegwan ShinKangmin ChonKyung Hwa Cho
- Topics
- Human Pose and Action Recognition (4 papers)Video Surveillance and Tracking Methods (4 papers)Advanced Vision and Imaging (3 papers)
- Partner nations
- South KoreaJapan
In The Last Decade
Sangwon Kim
26 papers receiving 386 citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 196
- Artificial Intelligence 111
- Biomedical Engineering 82
- Computer Networks and Communications 57
- Electrical and Electronic Engineering 50
Countries citing papers authored by Sangwon Kim
This map shows the geographic impact of Sangwon 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 Sangwon Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sangwon Kim more than expected).
Fields of papers citing papers by Sangwon Kim
This network shows the impact of papers produced by Sangwon 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 Sangwon Kim. The network helps show where Sangwon Kim may publish in the future.
Co-authorship network of co-authors of Sangwon Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Sangwon Kim. A scholar is included among the top collaborators of Sangwon 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 Sangwon Kim. Sangwon 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 | 14 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 67 | |
| 5 | STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognitionbreakdown → | 112 |
| 6 | 5 | |
| 7 | 21 | |
| 8 | 3 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 5 | |
| 12 | 10 | |
| 13 | 12 | |
| 14 | 11 | |
| 15 | 2 | |
| 16 | 10 | |
| 17 | Deep Coupling of Random Ferns. | 2 |
| 18 | 7 | |
| 19 | 4 | |
| 20 | 46 |
About Sangwon Kim
Sangwon Kim is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Signal Processing, having authored 26 papers that have together received 398 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (4 papers), Video Surveillance and Tracking Methods (4 papers) and Advanced Vision and Imaging (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (196 citations), Human-Computer Interaction (49 citations) and Artificial Intelligence (111 citations). Sangwon Kim has collaborated with scholars based in South Korea and Japan. Frequent co-authors include Byoung Chul Ko, Jae-Yeal Nam, Chang-Hyun Park, Zeeshan Haider Jaffari, Chang‐Min Kim, Jaegwan Shin, Kangmin Chon, Kyung Hwa Cho, Jinwoo Kwak and Changgil Son. Their work appears in journals such as Journal of Hazardous Materials, IEEE Access and Sensors.
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.