Dogyoon Lee
Impact in
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- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Advanced Vision and Imaging
- Human-Computer Interaction top 10%
- Hand Gesture Recognition Systems
Papers in
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- Visual Attention and Saliency Detection 4
- Advanced Image and Video Retrieval Techniques 3
- Advanced Neural Network Applications 3
- Advanced Image Processing Techniques 2
- Image Enhancement Techniques 1
- Geology 3
- 3D Surveying and Cultural Heritage 3
- Co-authors
- Sangyoun Lee (11 shared papers)Minhyeok Lee (4 shared papers)Sangwon Hwang (2 shared papers)Suhwan Cho (5 shared papers)Seunghoon Lee (2 shared papers)Ig-Jae Kim (1 shared paper)Heeseung Choi (1 shared paper)Taeoh Kim (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)ICT Express (1 paper)Pattern Recognition (1 paper)SSRN Electronic Journal (1 paper)
- Partner nations
- South KoreaUnited States
In The Last Decade
Dogyoon Lee
9 papers receiving 221 citations
Dogyoon Lee's Hit Papers
Peers
Comparison fields: 5 of 40
- Computer Vision and Pattern Recognition 174
- Human-Computer Interaction 41
- Computer Graphics and Computer-Aided Design 14
- Geology 19
- Artificial Intelligence 77
Countries citing papers authored by Dogyoon Lee
This map shows the geographic impact of Dogyoon 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 Dogyoon Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dogyoon Lee more than expected).
Fields of papers citing papers by Dogyoon Lee
This network shows the impact of papers produced by Dogyoon 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 Dogyoon Lee. The network helps show where Dogyoon Lee may publish in the future.
Co-authors
The 12 scholars most cited alongside Dogyoon Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action Recognition Hit paper breakdown → | 2023 | 147 |
| 2 | 2023 | 30 | |
| 3 | 2023 | 26 | |
| 4 | 2024 | 7 | |
| 5 | 2024 | 7 | |
| 6 | 2023 | 4 | |
| 7 | 2021 | 2 | |
| 8 | 2025 | 1 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 0 | |
| 11 | 2023 | 0 |
About Dogyoon Lee
Dogyoon Lee is a scholar working on Computer Vision and Pattern Recognition, Geology, Environmental Engineering, Atomic and Molecular Physics, and Optics and Computational Mechanics, having authored 11 papers that have together received 225 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (4 papers), 3D Surveying and Cultural Heritage (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers), Remote Sensing and LiDAR Applications (2 papers), Advanced Image Processing Techniques (2 papers), Robotics and Sensor-Based Localization (1 paper) and Image Enhancement Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (174 citations), Human-Computer Interaction (41 citations), Computer Graphics and Computer-Aided Design (14 citations), Geology (19 citations) and Artificial Intelligence (77 citations). Dogyoon Lee has collaborated with scholars based in South Korea and United States. Frequent co-authors include Sangyoun Lee, Minhyeok Lee, Sangwon Hwang, Suhwan Cho, Seunghoon Lee, Ig-Jae Kim, Heeseung Choi, Taeoh Kim, Chaewon Park and Jungho Lee. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ICT Express, Pattern Recognition and SSRN Electronic Journal.
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.