Ki‐Chul Kwon

1.6k citations
109 papers · 1.2k · h-index 21

Impact in

Papers in

Ki‐Chul Kwon

99 papers receiving 1.1k citations

Peers

Ki‐Chul Kwon
Comparison fields: 5 of 79
  • Media Technology 806
  • Human-Computer Interaction 354
  • Computer Vision and Pattern Recognition 437
  • Computer Graphics and Computer-Aided Design 74
  • Atomic and Molecular Physics, and Optics 460
Replace Shiro Suyama with:
Shiro Suyama Japan
Praneeth Chakravarthula United States
Sungyong Jung United States
Andrew Maimone United States
Phil Surman United Kingdom
Quinn Smithwick United States
Jonghyun Kim South Korea
Joel Kollin United States
Jun Arai Japan
Yan Xing China
Ki‐Chul Kwon relative to Shiro Suyama Japan Shiro Suyama's profile →
Citations per field
00.5×2×4×6.2×
Shiro Suyama · 1×
Citations per year

Countries citing papers authored by Ki‐Chul Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Ki‐Chul Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ki‐Chul Kwon. 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 Ki‐Chul Kwon. The network helps show where Ki‐Chul Kwon may publish in the future.

Co-authors

The 25 scholars most cited alongside Ki‐Chul Kwon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ki‐Chul Kwon Line = papers co-authored together Ki‐Chul Kwon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 109 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200974
2 202059
3 201252
4 202048
5 201742
6 201239
7 200937
8 201936
9 201332
10 201630
11 201529
12 201529
13 201729
14 201825
15 202023
16 201023
17 202122
18 202022
19 201722
20 201421

About Ki‐Chul Kwon

Ki‐Chul Kwon is a scholar working on Media Technology, Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition, Human-Computer Interaction and Biomedical Engineering, having authored 109 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Optical Imaging Technologies (76 papers), Digital Holography and Microscopy (28 papers), Virtual Reality Applications and Impacts (24 papers), Photorefractive and Nonlinear Optics (23 papers), Advanced Vision and Imaging (22 papers), Image Processing Techniques and Applications (16 papers), Computer Graphics and Visualization Techniques (9 papers) and Optical Coherence Tomography Applications (6 papers). The work is most often cited by research in Media Technology (806 citations), Human-Computer Interaction (354 citations), Computer Vision and Pattern Recognition (437 citations), Computer Graphics and Computer-Aided Design (74 citations) and Atomic and Molecular Physics, and Optics (460 citations). Ki‐Chul Kwon has collaborated with scholars based in South Korea, Mongolia and China. Frequent co-authors include Nam Kim, Munkh‐Uchral Erdenebat, Young-Tae Lim, Jae‐Hyeung Park, Kwan‐Hee Yoo, Ji‐Seong Jeong, Md. Shahinur Alam, Yu Zhao, Mei-Lan Piao and Ashraf A. M. Khalaf. Their work appears in journals such as Optics Express, Applied Optics, Sensors, Optics Letters and Optics & Laser Technology.

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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