Gui–Bo Ye
Impact in
-
- Image and Signal Denoising Methods
- Face and Expression Recognition
- Advanced Image Processing Techniques
Papers in
-
- Sparse and Compressive Sensing Techniques 6
-
- Face and Expression Recognition 2
- Image and Signal Denoising Methods 2
- Co-authors
- Jian‐Feng Cai (4 shared papers)Zuowei Shen (2 shared papers)Hui Ji (1 shared paper)Xiaohui Xie (2 shared papers)Ding‐Xuan Zhou (2 shared papers)Weiyu Xu (1 shared paper)Xiaobo Qu (1 shared paper)Qing Nie (1 shared paper)
- Journals
- Applied and Computational Harmonic Analysis (4 papers)Advances in Computational Mathematics (1 paper)Computational Statistics & Data Analysis (1 paper)PLoS ONE (1 paper)Machine Learning (1 paper)
- Partner nations
- United StatesHong KongChina
In The Last Decade
Gui–Bo Ye
9 papers receiving 405 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 217
- Computational Mathematics 6
- Computational Mechanics 204
- Statistics and Probability 53
- Media Technology 41
Countries citing papers authored by Gui–Bo Ye
This map shows the geographic impact of Gui–Bo Ye'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 Gui–Bo Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gui–Bo Ye more than expected).
Fields of papers citing papers by Gui–Bo Ye
This network shows the impact of papers produced by Gui–Bo Ye. 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 Gui–Bo Ye. The network helps show where Gui–Bo Ye may publish in the future.
Co-authors
The 9 scholars most cited alongside Gui–Bo Ye, 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 | 2013 | 199 | |
| 2 | 2010 | 67 | |
| 3 | 2016 | 43 | |
| 4 | 2007 | 33 | |
| 5 | Efficient variable selection in support vector machines via the alternating direction method of multipliers | 2011 | 31 |
| 6 | 2007 | 26 | |
| 7 | 2012 | 12 | |
| 8 | 2013 | 11 | |
| 9 | 2010 | 5 |
About Gui–Bo Ye
Gui–Bo Ye is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence and Applied Mathematics, having authored 9 papers that have together received 427 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (6 papers), Face and Expression Recognition (2 papers), Image and Signal Denoising Methods (2 papers), Statistical Methods and Inference (2 papers), Control Systems and Identification (2 papers), Mathematical Analysis and Transform Methods (2 papers), Bayesian Methods and Mixture Models (2 papers) and Animal Virus Infections Studies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (217 citations), Computational Mathematics (6 citations), Computational Mechanics (204 citations), Statistics and Probability (53 citations) and Media Technology (41 citations). Gui–Bo Ye has collaborated with scholars based in United States, Hong Kong and China. Frequent co-authors include Jian‐Feng Cai, Zuowei Shen, Hui Ji, Xiaohui Xie, Ding‐Xuan Zhou, Weiyu Xu, Xiaobo Qu, Xiaohui Xie and Qing Nie. Their work appears in journals such as Applied and Computational Harmonic Analysis, Advances in Computational Mathematics, Computational Statistics & Data Analysis, PLoS ONE and Machine Learning.
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.