Kuang-Chih Lee
- Computer Vision and Pattern Recognition top 0.2%
- Computational Mechanics top 1%
- Artificial Intelligence top 2%
- Signal Processing top 1%
- Media Technology top 0.5%
- Co-authors
- David KriegmanMing–Hsuan YangJongwoo LimJeffrey HoAli DasdanWentong LiDonghyuk ShinSuleyman Cetintas
- Topics
- Face and Expression Recognition (7 papers)Face recognition and analysis (6 papers)Recommender Systems and Techniques (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceMIS QuarterlyComputer Vision and Image Understanding
- Partner nations
- United StatesChinaCanada
In The Last Decade
Kuang-Chih Lee
29 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Computer Vision and Pattern Recognition 2.7k
- Computational Mechanics 806
- Artificial Intelligence 669
- Signal Processing 571
- Media Technology 512
Countries citing papers authored by Kuang-Chih Lee
This map shows the geographic impact of Kuang-Chih 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 Kuang-Chih Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuang-Chih Lee more than expected).
Fields of papers citing papers by Kuang-Chih Lee
This network shows the impact of papers produced by Kuang-Chih 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 Kuang-Chih Lee. The network helps show where Kuang-Chih Lee may publish in the future.
Co-authorship network of co-authors of Kuang-Chih Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Kuang-Chih Lee. A scholar is included among the top collaborators of Kuang-Chih Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kuang-Chih Lee. Kuang-Chih Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 9 | |
| 4 | 0 | |
| 5 | 140 | |
| 6 | 32 | |
| 7 | 9 | |
| 8 | 7 | |
| 9 | 3 | |
| 10 | 11 | |
| 11 | 23 | |
| 12 | 124 | |
| 13 | 8 | |
| 14 | Acquiring linear subspaces for face recognition under variable lightingbreakdown → | 1696 |
| 15 | 86 | |
| 16 | 10 | |
| 17 | 144 | |
| 18 | 123 | |
| 19 | 373 | |
| 20 | On Reducing the Complexity of Illumination Cones for Face Recognition | 2 |
About Kuang-Chih Lee
Kuang-Chih Lee is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Marketing, having authored 30 papers that have together received 3.4k indexed citations. Recurring topics across this work include Face and Expression Recognition (7 papers), Face recognition and analysis (6 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.7k citations), Computational Mathematics (72 citations) and Media Technology (512 citations). Kuang-Chih Lee has collaborated with scholars based in United States, China and Canada. Frequent co-authors include David Kriegman, Ming–Hsuan Yang, Jongwoo Lim, Jeffrey Ho, Ali Dasdan, Wentong Li, Donghyuk Shin, Suleyman Cetintas, Andrew B. Whinston and Gene Moo Lee. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, MIS Quarterly and Computer Vision and Image Understanding.
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.