Hyeonjun Sim
Impact in
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- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Generative Adversarial Networks and Image Synthesis
- Advanced Neural Network Applications
- Image and Signal Denoising Methods
- Advanced Vision and Imaging
Papers in
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- Advanced Image Processing Techniques 5
- Image Enhancement Techniques 3
- Generative Adversarial Networks and Image Synthesis 1
- Co-authors
- Munchurl Kim (5 shared papers)Jihyong Oh (1 shared paper)Soo Ye Kim (4 shared papers)Jae-Seok Choi (2 shared papers)Soomin Seo (2 shared papers)Saehun Kim (2 shared papers)Sehwan Ki (2 shared papers)Jae-Ho Lee (1 shared paper)
- Journals
- IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (6 papers)IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2 papers)
- Partner nations
- South KoreaChinaUnited States
In The Last Decade
Hyeonjun Sim
9 papers receiving 702 citations
Peers
Comparison fields: 5 of 32
- Computer Vision and Pattern Recognition 678
- Acoustics and Ultrasonics 3
- Media Technology 15
- Signal Processing 14
- Instrumentation 3
Countries citing papers authored by Hyeonjun Sim
This map shows the geographic impact of Hyeonjun Sim'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 Hyeonjun Sim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyeonjun Sim more than expected).
Fields of papers citing papers by Hyeonjun Sim
This network shows the impact of papers produced by Hyeonjun Sim. 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 Hyeonjun Sim. The network helps show where Hyeonjun Sim may publish in the future.
Co-authors
The 8 scholars most cited alongside Hyeonjun Sim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 265 | |
| 2 | 2021 | 139 | |
| 3 | 2018 | 126 | |
| 4 | 2021 | 67 | |
| 5 | 2019 | 37 | |
| 6 | 2019 | 34 | |
| 7 | 2018 | 25 | |
| 8 | 2018 | 24 | |
| 9 | 2023 | 10 |
About Hyeonjun Sim
Hyeonjun Sim is a scholar working on Computer Vision and Pattern Recognition, Nuclear Energy and Engineering, Waste Management and Disposal, Infectious Diseases and Organic Chemistry, having authored 9 papers that have together received 727 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (5 papers), Image Enhancement Techniques (3 papers) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (678 citations), Acoustics and Ultrasonics (3 citations), Media Technology (15 citations), Signal Processing (14 citations) and Instrumentation (3 citations). Hyeonjun Sim has collaborated with scholars based in South Korea, China and United States. Frequent co-authors include Munchurl Kim, Jihyong Oh, Soo Ye Kim, Jae-Seok Choi, Soomin Seo, Saehun Kim, Sehwan Ki and Jae-Ho Lee. Their work appears in journals such as IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE/CVF International Conference on Computer Vision (ICCV) and IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings.
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.