Sunghyun Cho

5.1k citations
51 papers · 2.6k indexed · 2 hit papers · h-index 20
Topics
Advanced Image Processing Techniques (31 papers)Advanced Vision and Imaging (26 papers)Image and Signal Denoising Methods (18 papers)

In The Last Decade

Sunghyun Cho

44 papers receiving 2.5k citations

Hit Papers

Fast motion deblurring200920262014202020092019200400600

Peers

Sunghyun Cho
Comparison fields: 5 of 98
  • Computer Vision and Pattern Recognition 2.4k
  • Media Technology 1.3k
  • Artificial Intelligence 247
  • Computational Mechanics 143
  • Atomic and Molecular Physics, and Optics 75
Replace Yacov Hel-Or with:
Yacov Hel-Or Israel
Ayan Chakrabarti United States
Jiawei Zhang China
Seungjun Nah South Korea
Hongwei Yong Hong Kong
Longguang Wang China
Jianrui Cai Hong Kong
Daniel Gläsner United States
Wenxiu Sun Hong Kong
Shuying Huang China
Sunghyun Cho relative to Yacov Hel-Or Israel Yacov Hel-Or's profile →
Citations per field
00.5×7.3×
Yacov Hel-Or · 1×
Citations per year

Countries citing papers authored by Sunghyun Cho

Since Specialization
Citations

This map shows the geographic impact of Sunghyun Cho'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 Sunghyun Cho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunghyun Cho more than expected).

Fields of papers citing papers by Sunghyun Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunghyun Cho. 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 Sunghyun Cho. The network helps show where Sunghyun Cho may publish in the future.

Co-authorship network of co-authors of Sunghyun Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Sunghyun Cho. A scholar is included among the top collaborators of Sunghyun Cho 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 Sunghyun Cho. Sunghyun Cho is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 2
4 1
5 5
6 17
7 0
8 5
9 12
10 8
11 41
12 101
13 2
14 134
15 146
16 3
17 2
18 71
19 226
20 114

About Sunghyun Cho

Sunghyun Cho is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Graphics and Computer-Aided Design, having authored 51 papers that have together received 2.6k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (31 papers), Advanced Vision and Imaging (26 papers) and Image and Signal Denoising Methods (18 papers). The work is most often cited by research in Media Technology (1.3k citations), Computer Vision and Pattern Recognition (2.4k citations) and Acoustics and Ultrasonics (15 citations). Sunghyun Cho has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Seungyong Lee, Jue Wang, Suha Kwak, Yasuyuki Matsushita, Junyong Lee, Ming–Hsuan Yang, Zhe Hu, Lin Zhong, Dimitris Metaxas and Sylvain Paris. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Biomaterials and IEEE Access.

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.

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