Soo Ye Kim

896 citations
14 papers · 243 indexed · h-index 7
Topics
Advanced Vision and Imaging (6 papers)Advanced Image Processing Techniques (5 papers)Image Enhancement Techniques (4 papers)
Journals
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Rare & Special e-Zone (The Hong Kong University of Science and Technology)Proceedings of the AAAI Conference on Artificial Intelligence

In The Last Decade

Soo Ye Kim

12 papers receiving 234 citations

Peers

Soo Ye Kim
Comparison fields: 5 of 33
  • Computer Vision and Pattern Recognition 222
  • Media Technology 96
  • Computer Graphics and Computer-Aided Design 14
  • Computational Mechanics 10
  • Control and Systems Engineering 9
Replace Eduardo Pérez-Pellitero with:
Eduardo Pérez-Pellitero Germany
Xinchen Ye China
Xuanhong Chen China
Guilherme V. Cavalheiro United States
Mahyar Najibi United States
Lang Nie China
Deqing Sun United States
Hengyuan Zhao China
Jan Kotera Czechia
Majed El Helou Switzerland
Soo Ye Kim relative to Eduardo Pérez-Pellitero Germany Eduardo Pérez-Pellitero's profile →
Citations per field
00.5×3.6×
Eduardo Pérez-Pellitero · 1×
Citations per year

Countries citing papers authored by Soo Ye Kim

Since Specialization
Citations

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

Fields of papers citing papers by Soo Ye Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soo Ye 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 Soo Ye Kim. The network helps show where Soo Ye Kim may publish in the future.

Co-authorship network of co-authors of Soo Ye Kim

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 2
2 3
3 0
4 0
5 1
6 6
7 8
8 26
9 4
10 58
11 35
12 70
13 16
14 14

About Soo Ye Kim

Soo Ye Kim is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Media Technology, having authored 14 papers that have together received 243 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (6 papers), Advanced Image Processing Techniques (5 papers) and Image Enhancement Techniques (4 papers). The work is most often cited by research in Media Technology (96 citations), Computer Vision and Pattern Recognition (222 citations) and Computer Graphics and Computer-Aided Design (14 citations). Soo Ye Kim has collaborated with scholars based in United States, South Korea and Hong Kong. Frequent co-authors include Munchurl Kim, Hyeonjun Sim, Zhe Lin, Sehwan Ki, Yizhi Song, Scott Cohen, Brian Price, Jianming Zhang, Soomin Seo and Saehun Kim. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Proceedings of the AAAI Conference on Artificial Intelligence.

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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