QingE Wu
Impact in
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- Image Enhancement Techniques
- Advanced Neural Network Applications
- Media Technology top 10%
- Advanced Image Fusion Techniques
Papers in
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- Advanced Image and Video Retrieval Techniques 6
- Face and Expression Recognition 5
- Image Enhancement Techniques 5
- Advanced Neural Network Applications 4
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- Fuzzy Logic and Control Systems 6
- Co-authors
- Dan Nathan-Roberts (1 shared paper)Xiaoliang Qian (11 shared papers)Jinhua Liu (2 shared papers)Lihua Bi (2 shared papers)Ammar Belatreche (1 shared paper)Hu Chen (8 shared papers)Liam Maguire (1 shared paper)T.M. McGinnity (1 shared paper)
- Journals
- Applied Sciences (4 papers)Scientific Reports (3 papers)Electronics (3 papers)IEEE Access (2 papers)Arabian Journal for Science and Engineering (2 papers)
- Partner nations
- ChinaUnited StatesRussia
In The Last Decade
QingE Wu
60 papers receiving 370 citations
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 106
- Media Technology 41
- Industrial and Manufacturing Engineering 33
- Computational Theory and Mathematics 52
- Control and Systems Engineering 60
Countries citing papers authored by QingE Wu
This map shows the geographic impact of QingE 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 QingE Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites QingE Wu more than expected).
Fields of papers citing papers by QingE Wu
This network shows the impact of papers produced by QingE 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 QingE Wu. The network helps show where QingE Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside QingE 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 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 41 | |
| 2 | 2016 | 31 | |
| 3 | A Method for Supervised Training of Spiking Neural Networks | 2003 | 28 |
| 4 | 2020 | 20 | |
| 5 | 2018 | 20 | |
| 6 | 2018 | 19 | |
| 7 | 2023 | 13 | |
| 8 | 2019 | 13 | |
| 9 | 2022 | 13 | |
| 10 | 2010 | 12 | |
| 11 | 2019 | 11 | |
| 12 | 2017 | 10 | |
| 13 | 2023 | 10 | |
| 14 | 2023 | 9 | |
| 15 | 2019 | 9 | |
| 16 | 2023 | 8 | |
| 17 | 2023 | 8 | |
| 18 | 2008 | 7 | |
| 19 | 2020 | 7 | |
| 20 | 2013 | 7 |
About QingE Wu
QingE Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Media Technology and Aerospace Engineering, having authored 73 papers that have together received 383 indexed citations. Recurring topics across this work include Fault Detection and Control Systems (7 papers), Fuzzy Logic and Control Systems (6 papers), Advanced Image and Video Retrieval Techniques (6 papers), Industrial Vision Systems and Defect Detection (5 papers), Face and Expression Recognition (5 papers), Image Enhancement Techniques (5 papers), Advanced Neural Network Applications (4 papers) and Machine Fault Diagnosis Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (106 citations), Media Technology (41 citations), Industrial and Manufacturing Engineering (33 citations), Computational Theory and Mathematics (52 citations) and Control and Systems Engineering (60 citations). QingE Wu has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Dan Nathan-Roberts, Xiaoliang Qian, Jinhua Liu, Lihua Bi, Ammar Belatreche, Hu Chen, Liam Maguire, T.M. McGinnity, Huanlong Zhang and Cunxiang Yang. Their work appears in journals such as Applied Sciences, Scientific Reports, Electronics, IEEE Access and Arabian Journal for Science and 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.