Won‐Sook Lee

69 papers receiving 645 citations

Peers

Won‐Sook Lee
Comparison fields: 5 of 110
  • Signal Processing 150
  • Computer Graphics and Computer-Aided Design 44
  • Computer Vision and Pattern Recognition 249
  • Human-Computer Interaction 61
  • Cognitive Neuroscience 115
Replace Min‐Chun Hu with:
Min‐Chun Hu Taiwan
Aihua Mao China
Zhiquan Feng China
Liqian Ma China
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Matthias Rätsch Germany
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Citations per field
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Citations per year

Countries citing papers authored by Won‐Sook Lee

Since Specialization
Citations

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

Fields of papers citing papers by Won‐Sook Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Disambiguating Music Emotion Using Software Agents.
200469
2 200951
3 201542
4
MODEL BASED FACE RECONSTRUCTION FOR ANIMATION
199935
5 200731
6 202030
7 201027
8 201725
9 201521
10 200921
11 201420
12 201319
13 202217
14 201816
15 202214
16 200714
17 201914
18 200614
19 201813
20 200813

About Won‐Sook Lee

Won‐Sook Lee is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Artificial Intelligence, Computer Graphics and Computer-Aided Design and Control and Systems Engineering, having authored 72 papers that have together received 676 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (15 papers), Computer Graphics and Visualization Techniques (12 papers), Face recognition and analysis (12 papers), Advanced Vision and Imaging (11 papers), Human Motion and Animation (8 papers), Traditional Chinese Medicine Studies (6 papers), Teleoperation and Haptic Systems (6 papers) and Speech and Audio Processing (6 papers). The work is most often cited by research in Signal Processing (150 citations), Computer Graphics and Computer-Aided Design (44 citations), Computer Vision and Pattern Recognition (249 citations), Human-Computer Interaction (61 citations) and Cognitive Neuroscience (115 citations). Won‐Sook Lee has collaborated with scholars based in Canada, United States and Switzerland. Frequent co-authors include M. Hamed Mozaffari, Kaveh Hassani, Jochen Lang, Pengcheng Xi, Chang Shu, Nadia Magnenat‐Thalmann, Prem Kalra, Paul E. Beaulé, Yoon Ko and Yuchuan Li. Their work appears in journals such as The Visual Computer, The Journal of the Acoustical Society of America, Virtual Reality, Medical Image Analysis and International journal of computational fluid dynamics.

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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