Wei Wu
Impact in
- Artificial Intelligence top 2%
- Neural Networks and Applications
- Machine Learning and ELM
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- Face and Expression Recognition
Papers in
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- Neural Networks and Applications 33
- Machine Learning and ELM 27
- Fuzzy Logic and Control Systems 8
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- Advanced Memory and Neural Computing 10
- Electromagnetic Compatibility and Noise Suppression 7
- Co-authors
- Jie Yang (20 shared papers)Jacek M. Żurada (7 shared papers)Junhong Zhao (4 shared papers)Jian Wang (6 shared papers)Qinwei Fan (5 shared papers)Yanyan Cao (5 shared papers)Jonathan V. Caspar (5 shared papers)Kaushik Roy Choudhury (4 shared papers)
- Journals
- Neurocomputing (10 papers)Neural Processing Letters (6 papers)IEEE Access (2 papers)Neural Computing and Applications (2 papers)Neural Networks (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Wei Wu
116 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 811
- Computer Vision and Pattern Recognition 301
- Electrical and Electronic Engineering 731
- Computational Mathematics 6
- Control and Systems Engineering 214
Countries citing papers authored by Wei Wu
This map shows the geographic impact of Wei Wu'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 Wei Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Wu more than expected).
Fields of papers citing papers by Wei Wu
This network shows the impact of papers produced by Wei Wu. 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 Wei Wu. The network helps show where Wei Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Wu, 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 133 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 300 | |
| 2 | 2016 | 179 | |
| 3 | 2019 | 135 | |
| 4 | 2005 | 127 | |
| 5 | 2015 | 72 | |
| 6 | 2013 | 63 | |
| 7 | 2014 | 63 | |
| 8 | 2017 | 53 | |
| 9 | 2012 | 48 | |
| 10 | 2011 | 45 | |
| 11 | 1987 | 43 | |
| 12 | 2002 | 43 | |
| 13 | 2013 | 43 | |
| 14 | 2011 | 39 | |
| 15 | 2018 | 36 | |
| 16 | 2017 | 34 | |
| 17 | 2014 | 34 | |
| 18 | 2011 | 32 | |
| 19 | 2008 | 25 | |
| 20 | 2021 | 21 |
About Wei Wu
Wei Wu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering and Computational Mechanics, having authored 133 papers that have together received 2.1k indexed citations. Recurring topics across this work include Neural Networks and Applications (33 papers), Machine Learning and ELM (27 papers), Advanced Memory and Neural Computing (10 papers), Image and Signal Denoising Methods (9 papers), Face and Expression Recognition (8 papers), Fuzzy Logic and Control Systems (8 papers), Sparse and Compressive Sensing Techniques (7 papers) and Electromagnetic Compatibility and Noise Suppression (7 papers). The work is most often cited by research in Artificial Intelligence (811 citations), Computer Vision and Pattern Recognition (301 citations), Electrical and Electronic Engineering (731 citations), Computational Mathematics (6 citations) and Control and Systems Engineering (214 citations). Wei Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jie Yang, Jacek M. Żurada, Junhong Zhao, Jian Wang, Qinwei Fan, Yanyan Cao, Jonathan V. Caspar, Kaushik Roy Choudhury, Qijie Guo and Lynda K. Johnson. Their work appears in journals such as Neurocomputing, Neural Processing Letters, IEEE Access, Neural Computing and Applications and Neural Networks.
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.