Dar-Shyang Lee
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- Handwritten Text Recognition Techniques 9
- Video Analysis and Summarization 8
- Video Surveillance and Tracking Methods 3
- Image Processing and 3D Reconstruction 2
- Media Technology top 5%
- Signal Processing top 10%
- Music and Audio Processing 6
- Speech and Audio Processing 2
- Artificial Intelligence top 5%
- Natural Language Processing Techniques 3
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- Multimedia Communication and Technology 4
Dar-Shyang Lee
21 papers receiving 947 citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 856
- Media Technology 114
- Signal Processing 89
- Safety, Risk, Reliability and Quality 66
- Artificial Intelligence 222
Countries citing papers authored by Dar-Shyang Lee
This map shows the geographic impact of Dar-Shyang 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 Dar-Shyang Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dar-Shyang Lee more than expected).
Fields of papers citing papers by Dar-Shyang Lee
This network shows the impact of papers produced by Dar-Shyang 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 Dar-Shyang Lee. The network helps show where Dar-Shyang Lee may publish in the future.
Co-authorship network
The 10 scholars most cited alongside Dar-Shyang 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 | 2020 | 1 | |
| 2 | 2012 | 7 | |
| 3 | 2009 | 75 | |
| 4 | Effective Gaussian mixture learning for video background subtractionbreakdown → | 2005 | 614 |
| 5 | 2004 | 79 | |
| 6 | 2004 | 4 | |
| 7 | 2004 | 1 | |
| 8 | 2003 | 20 | |
| 9 | 2003 | 0 | |
| 10 | 2003 | 10 | |
| 11 | 2003 | 8 | |
| 12 | Improved Adaptive Mixture Learning for Robust Video Background Modeling. | 2002 | 13 |
| 13 | 2002 | 10 | |
| 14 | 2002 | 1 | |
| 15 | 2002 | 54 | |
| 16 | 2002 | 13 | |
| 17 | 2002 | 4 | |
| 18 | 2001 | 5 | |
| 19 | 1995 | 4 | |
| 20 | Neural network models and their application to handwritten digit recognition. | 1988 | 12 |
About Dar-Shyang Lee
Dar-Shyang Lee is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 22 papers that have together received 1.0k indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (9 papers), Video Analysis and Summarization (8 papers), Music and Audio Processing (6 papers), Multimedia Communication and Technology (4 papers), Video Surveillance and Tracking Methods (3 papers), Natural Language Processing Techniques (3 papers), Speech and Audio Processing (2 papers) and Image Processing and 3D Reconstruction (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (856 citations), Media Technology (114 citations) and Signal Processing (89 citations). Dar-Shyang Lee has collaborated with scholars based in United States and Japan. Frequent co-authors include Sargur N. Srihari, Ray Smith, Jonathan J. Hull, B. Erol, J.J. Hull, Jamey Graham, Yongchul Shin, Sargur Srihari, Steven L. Schwarcz and Alexander N. Gorban. Their work appears in journals such as Machine Vision and Applications, Pattern Recognition Letters, Proceedings of the IEEE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.