Minghu Wu
Impact in
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- Control Systems and Identification
- Fault Detection and Control Systems
- Automotive Engineering top 10%
- Advanced Battery Technologies Research
Papers in
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- Advanced Neural Network Applications 5
- Digital Imaging for Blood Diseases 4
- Image Enhancement Techniques 4
- Co-authors
- Nan Zhao (7 shared papers)Jingjing Chen (1 shared paper)Xiangkui Wan (3 shared papers)Fan Zhang (2 shared papers)Min Liu (6 shared papers)Yinhua Xia (1 shared paper)Jin Liang (1 shared paper)Yan Li (1 shared paper)
In The Last Decade
Minghu Wu
50 papers receiving 766 citations
Peers
Comparison fields: 5 of 94
- Control and Systems Engineering 374
- Automotive Engineering 123
- Artificial Intelligence 245
- Computer Vision and Pattern Recognition 155
- Civil and Structural Engineering 99
Countries citing papers authored by Minghu Wu
This map shows the geographic impact of Minghu 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 Minghu Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minghu Wu more than expected).
Fields of papers citing papers by Minghu Wu
This network shows the impact of papers produced by Minghu 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 Minghu Wu. The network helps show where Minghu Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Minghu 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 115 | |
| 2 | 2016 | 91 | |
| 3 | 2020 | 83 | |
| 4 | 2022 | 61 | |
| 5 | 2016 | 47 | |
| 6 | 2023 | 39 | |
| 7 | 2018 | 39 | |
| 8 | 2017 | 34 | |
| 9 | 2021 | 30 | |
| 10 | 2022 | 27 | |
| 11 | 2022 | 23 | |
| 12 | 2022 | 18 | |
| 13 | 2021 | 18 | |
| 14 | 2021 | 15 | |
| 15 | 2024 | 14 | |
| 16 | 2019 | 11 | |
| 17 | 2021 | 11 | |
| 18 | 2024 | 8 | |
| 19 | 2013 | 8 | |
| 20 | 2015 | 8 |
About Minghu Wu
Minghu Wu is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Control and Systems Engineering, Biomedical Engineering and Automotive Engineering, having authored 56 papers that have together received 793 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (7 papers), Fault Detection and Control Systems (6 papers), Advanced Battery Technologies Research (6 papers), Advanced Neural Network Applications (5 papers), AI in cancer detection (5 papers), Digital Imaging for Blood Diseases (4 papers), Cooperative Communication and Network Coding (4 papers) and Image Enhancement Techniques (4 papers). The work is most often cited by research in Control and Systems Engineering (374 citations), Automotive Engineering (123 citations), Artificial Intelligence (245 citations), Computer Vision and Pattern Recognition (155 citations) and Civil and Structural Engineering (99 citations). Minghu Wu has collaborated with scholars based in China, Canada and Australia. Frequent co-authors include Nan Zhao, Jingjing Chen, Xiangkui Wan, Fan Zhang, Min Liu, Yinhua Xia, Jin Liang, Yan Li, Chunyan Zeng and Cong Liu. Their work appears in journals such as CAAI Transactions on Intelligence Technology, Electronics, Journal of Energy Storage, Pattern Analysis and Applications and PeerJ Computer Science.
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.