Yuh‐Jye Lee
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Control and Systems Engineering top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Co-authors
- O. L. MangasarianSu‐Yun HuangYi-Ren YehYu-Chiang Frank WangHsing-Kuo PaoWolfgang Karl HärdleDorothea SchäferTsung-Ju Lee
- Topics
- Face and Expression Recognition (17 papers)Network Security and Intrusion Detection (10 papers)Neural Networks and Applications (8 papers)
- Partner nations
- TaiwanUnited StatesGermany
In The Last Decade
Yuh‐Jye Lee
39 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 1.0k
- Computer Vision and Pattern Recognition 727
- Control and Systems Engineering 294
- Computer Networks and Communications 234
- Signal Processing 221
Countries citing papers authored by Yuh‐Jye Lee
This map shows the geographic impact of Yuh‐Jye 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 Yuh‐Jye Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuh‐Jye Lee more than expected).
Fields of papers citing papers by Yuh‐Jye Lee
This network shows the impact of papers produced by Yuh‐Jye 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 Yuh‐Jye Lee. The network helps show where Yuh‐Jye Lee may publish in the future.
Co-authorship network of co-authors of Yuh‐Jye Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Yuh‐Jye Lee. A scholar is included among the top collaborators of Yuh‐Jye 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 Yuh‐Jye Lee. Yuh‐Jye 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 | 20 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | A Review of Reduced Kernel Trick in Machine Learning | 2 |
| 6 | 12 | |
| 7 | Solving Nonlinear SVM in Linear Time? A Nystrom Approximated SVM with Applications to Image Classification ∗ | 0 |
| 8 | 33 | |
| 9 | 13 | |
| 10 | 5 | |
| 11 | 17 | |
| 12 | 20 | |
| 13 | 1 | |
| 14 | Periodic Step Size Adaptation for Single Pass On-line Learning | 1 |
| 15 | 14 | |
| 16 | 62 | |
| 17 | 56 | |
| 18 | 27 | |
| 19 | 191 | |
| 20 | 360 |
About Yuh‐Jye Lee
Yuh‐Jye Lee is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 44 papers that have together received 1.7k indexed citations. Recurring topics across this work include Face and Expression Recognition (17 papers), Network Security and Intrusion Detection (10 papers) and Neural Networks and Applications (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (727 citations), Artificial Intelligence (1.0k citations) and Signal Processing (221 citations). Yuh‐Jye Lee has collaborated with scholars based in Taiwan, United States and Germany. Frequent co-authors include O. L. Mangasarian, Su‐Yun Huang, Yi-Ren Yeh, Yu-Chiang Frank Wang, Hsing-Kuo Pao, Wolfgang Karl Härdle, Dorothea Schäfer, Tsung-Ju Lee, Yu-Wei Chao and Yu‐Wen Chen. Their work appears in journals such as Pattern Recognition, Neurocomputing and IEEE Transactions on Knowledge and Data Engineering.
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.