Seo-Won Ji
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 2%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Aerospace Engineering
- Co-authors
- Sung-Jea KoJun-Pyo HongSeung‐Won JungSung‐Jin ChoSeung-Jin BaekYong-Goo ShinSeung‐Wook KimSeungwook Kim
- Topics
- Advanced Image Processing Techniques (8 papers)Image Processing Techniques and Applications (7 papers)Image and Signal Denoising Methods (5 papers)
- Journals
- IEEE Access2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- South Korea
In The Last Decade
Seo-Won Ji
11 papers receiving 491 citations
Hit Papers
Peers
Comparison fields: 5 of 54
- Computer Vision and Pattern Recognition 447
- Media Technology 221
- Electrical and Electronic Engineering 24
- Biomedical Engineering 21
- Aerospace Engineering 20
Countries citing papers authored by Seo-Won Ji
This map shows the geographic impact of Seo-Won Ji'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 Seo-Won Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seo-Won Ji more than expected).
Fields of papers citing papers by Seo-Won Ji
This network shows the impact of papers produced by Seo-Won Ji. 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 Seo-Won Ji. The network helps show where Seo-Won Ji may publish in the future.
Co-authorship network of co-authors of Seo-Won Ji
This figure shows the co-authorship network connecting the top 25 collaborators of Seo-Won Ji. A scholar is included among the top collaborators of Seo-Won Ji 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 Seo-Won Ji. Seo-Won Ji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 29 | |
| 2 | Rethinking Coarse-to-Fine Approach in Single Image Deblurringbreakdown → | 424 |
| 3 | 5 | |
| 4 | 3 | |
| 5 | 12 | |
| 6 | 8 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 0 | |
| 10 | 12 | |
| 11 | 1 | |
| 12 | 4 |
About Seo-Won Ji
Seo-Won Ji is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Human-Computer Interaction, having authored 12 papers that have together received 502 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (8 papers), Image Processing Techniques and Applications (7 papers) and Image and Signal Denoising Methods (5 papers). The work is most often cited by research in Media Technology (221 citations), Computer Vision and Pattern Recognition (447 citations) and Acoustics and Ultrasonics (5 citations). Seo-Won Ji has collaborated with scholars based in South Korea. Frequent co-authors include Sung-Jea Ko, Jun-Pyo Hong, Seung‐Won Jung, Sung‐Jin Cho, Seung-Jin Baek, Yong-Goo Shin, Seung‐Wook Kim, Seungwook Kim, Jeongmin Lee and Sang‐Won Lee. Their work appears in journals such as IEEE Access, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.