Xinjun Peng
Impact in
-
- Face and Expression Recognition
- Artificial Intelligence top 2%
- Machine Learning and ELM
- Text and Document Classification Technologies
- Neural Networks and Applications
Papers in
-
- Face and Expression Recognition 37
- Image Retrieval and Classification Techniques 6
-
- Advanced Algorithms and Applications 21
- Co-authors
- Dong Xu (21 shared papers)De Chen (6 shared papers)Yifei Wang (1 shared paper)Jindong Shen (1 shared paper)Yifei Wang (2 shared papers)Wen Zhou (3 shared papers)Yifei Wang (3 shared papers)Xiang Liu (1 shared paper)
- Journals
- Neurocomputing (11 papers)Information Sciences (10 papers)Expert Systems with Applications (4 papers)Neural Computing and Applications (4 papers)International Journal of Machine Learning and Cybernetics (3 papers)
- Partner nations
- China
In The Last Decade
Xinjun Peng
46 papers receiving 1.5k citations
Xinjun Peng's Hit Papers
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 1.0k
- Artificial Intelligence 917
- Control and Systems Engineering 463
- Analytical Chemistry 135
- Media Technology 124
Countries citing papers authored by Xinjun Peng
This map shows the geographic impact of Xinjun Peng'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 Xinjun Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinjun Peng more than expected).
Fields of papers citing papers by Xinjun Peng
This network shows the impact of papers produced by Xinjun Peng. 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 Xinjun Peng. The network helps show where Xinjun Peng may publish in the future.
Co-authors
The 10 scholars most cited alongside Xinjun Peng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | TSVR: An efficient Twin Support Vector Machine for regression Hit paper breakdown → | 2009 | 399 |
| 2 | 2011 | 197 | |
| 3 | 2010 | 126 | |
| 4 | 2012 | 70 | |
| 5 | 2010 | 64 | |
| 6 | 2011 | 53 | |
| 7 | 2011 | 51 | |
| 8 | 2012 | 43 | |
| 9 | 2009 | 41 | |
| 10 | 2016 | 36 | |
| 11 | 2014 | 34 | |
| 12 | 2014 | 33 | |
| 13 | 2018 | 33 | |
| 14 | 2013 | 31 | |
| 15 | 2010 | 26 | |
| 16 | 2013 | 25 | |
| 17 | 2011 | 22 | |
| 18 | 2013 | 21 | |
| 19 | 2007 | 21 | |
| 20 | 2012 | 20 |
About Xinjun Peng
Xinjun Peng is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence, Media Technology and Analytical Chemistry, having authored 47 papers that have together received 1.6k indexed citations. Recurring topics across this work include Face and Expression Recognition (37 papers), Advanced Algorithms and Applications (21 papers), Machine Learning and ELM (8 papers), Neural Networks and Applications (7 papers), Remote-Sensing Image Classification (7 papers), Image Retrieval and Classification Techniques (6 papers), Gene Regulatory Network Analysis (5 papers) and Metaheuristic Optimization Algorithms Research (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.0k citations), Artificial Intelligence (917 citations), Control and Systems Engineering (463 citations), Analytical Chemistry (135 citations) and Media Technology (124 citations). Xinjun Peng has collaborated with scholars based in China. Frequent co-authors include Dong Xu, De Chen, Yifei Wang, Jindong Shen, Yifei Wang, Wen Zhou, Yifei Wang, Yifei Wang, Yifei Wang and Xiang Liu. Their work appears in journals such as Neurocomputing, Information Sciences, Expert Systems with Applications, Neural Computing and Applications and International Journal of Machine Learning and Cybernetics.
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.