Jong Beom
- Computer Vision and Pattern Recognition top 1%
- Radiology, Nuclear Medicine and Imaging top 5%
- Biomedical Engineering top 10%
- Media Technology top 2%
- Signal Processing top 5%
- Co-authors
- Byung Cheol SongJae‐Hak LeeWoo Hyun NamJaeyoun YiJae Young LeeSeok Bong YooDae Chul SuhSung Min Kwon
- Topics
- Advanced Vision and Imaging (40 papers)Medical Imaging Techniques and Applications (29 papers)Medical Image Segmentation Techniques (24 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyRadiology, Nuclear Medicine and Imaging
- Journals
- IEEE Transactions on Image ProcessingIEEE Transactions on Medical ImagingIEEE Journal of Solid-State Circuits
- Partner nations
- South KoreaUnited States
In The Last Decade
Jong Beom
118 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 86
- Computer Vision and Pattern Recognition 747
- Radiology, Nuclear Medicine and Imaging 336
- Biomedical Engineering 287
- Media Technology 197
- Signal Processing 131
Countries citing papers authored by Jong Beom
This map shows the geographic impact of Jong Beom'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 Jong Beom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jong Beom more than expected).
Fields of papers citing papers by Jong Beom
This network shows the impact of papers produced by Jong Beom. 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 Jong Beom. The network helps show where Jong Beom may publish in the future.
Co-authorship network of co-authors of Jong Beom
This figure shows the co-authorship network connecting the top 25 collaborators of Jong Beom. A scholar is included among the top collaborators of Jong Beom 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 Jong Beom. Jong Beom is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 12 | |
| 3 | 37 | |
| 4 | 16 | |
| 5 | 14 | |
| 6 | 1 | |
| 7 | 11 | |
| 8 | 58 | |
| 9 | 6 | |
| 10 | 2 | |
| 11 | 31 | |
| 12 | Registration of CT-ultrasound images of the liver based on efficient vessel-filtering and automatic Initial transform prediction | 2 |
| 13 | 13 | |
| 14 | 1 | |
| 15 | 4 | |
| 16 | 6 | |
| 17 | 21 | |
| 18 | Efficient Image Segmentation Preserving Semantic Object Shapes | 4 |
| 19 | 0 | |
| 20 | 5 |
About Jong Beom
Jong Beom is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Media Technology, having authored 124 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (40 papers), Medical Imaging Techniques and Applications (29 papers) and Medical Image Segmentation Techniques (24 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (747 citations), Media Technology (197 citations) and Radiology, Nuclear Medicine and Imaging (336 citations). Jong Beom has collaborated with scholars based in South Korea and United States. Frequent co-authors include Byung Cheol Song, Jae‐Hak Lee, Woo Hyun Nam, Jaeyoun Yi, Jae Young Lee, Seok Bong Yoo, Dae Chul Suh, Sung Min Kwon, Ji Hye Kim and Jin Kook Kim. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging and IEEE Journal of Solid-State Circuits.
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.