Suk‐Hwan Lee

2.2k citations
188 papers · 1.4k · h-index 18

Impact in

Papers in

Suk‐Hwan Lee

160 papers receiving 1.3k citations

Peers

Suk‐Hwan Lee
Comparison fields: 5 of 134
  • Computer Vision and Pattern Recognition 871
  • Computer Graphics and Computer-Aided Design 123
  • Artificial Intelligence 385
  • Biophysics 60
  • Media Technology 74
Replace Ki‐Ryong Kwon with:
Ki‐Ryong Kwon South Korea
Wee Kheng Leow Singapore
Ronghang Hu United States
Lei He China
Liujuan Cao China
Sergey Ablameyko Belarus
Yuqing Song China
Renjie Liao Canada
Xu Jia China
Xuequan Lu Australia
Suk‐Hwan Lee relative to Ki‐Ryong Kwon South Korea Ki‐Ryong Kwon's profile →
Citations per field
00.5×
Ki‐Ryong Kwon · 1×
Citations per year

Countries citing papers authored by Suk‐Hwan Lee

Since Specialization
Citations

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

Fields of papers citing papers by Suk‐Hwan Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Suk‐Hwan Lee. 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 Suk‐Hwan Lee. The network helps show where Suk‐Hwan Lee may publish in the future.

Co-authors

The 25 scholars most cited alongside Suk‐Hwan Lee, 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 Suk‐Hwan Lee Line = papers co-authored together Suk‐Hwan Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 188 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201889
2 202284
3 201869
4 201761
5 201143
6 201543
7 201439
8 200531
9 202129
10 202022
11 201921
12 201021
13 201319
14 202219
15 200419
16 201818
17 201218
18 200717
19 202217
20 201915

About Suk‐Hwan Lee

Suk‐Hwan Lee is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Computer Graphics and Computer-Aided Design and Computer Networks and Communications, having authored 188 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (57 papers), Chaos-based Image/Signal Encryption (25 papers), Advanced Image and Video Retrieval Techniques (20 papers), Computer Graphics and Visualization Techniques (19 papers), Video Analysis and Summarization (14 papers), DNA and Biological Computing (13 papers), Algorithms and Data Compression (12 papers) and 3D Shape Modeling and Analysis (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (871 citations), Computer Graphics and Computer-Aided Design (123 citations), Artificial Intelligence (385 citations), Biophysics (60 citations) and Media Technology (74 citations). Suk‐Hwan Lee has collaborated with scholars based in South Korea, United States and Vietnam. Frequent co-authors include Ki‐Ryong Kwon, Kwang-Seok Moon, Eung-Joo Lee, Oh‐Heum Kwon, Kyung-Won Kang, Thanh Tran, Sanghun Lim, Jin‐Hyeok Park, XiaoJiao Huo and Taesu Kim. Their work appears in journals such as Electronics, Applied Sciences, Sensors, Digital Signal Processing and Multimedia Tools and Applications.

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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