Mingyu Fan
Impact in
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- Face and Expression Recognition
- Video Surveillance and Tracking Methods
- Computational Mathematics top 10%
Papers in
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- Face and Expression Recognition 27
- Video Surveillance and Tracking Methods 14
- Advanced Image and Video Retrieval Techniques 8
- Robotic Path Planning Algorithms 5
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- Anomaly Detection Techniques and Applications 6
- Co-authors
- Xiaoqin Zhang (16 shared papers)Peng Zhou (5 shared papers)Liang Du (7 shared papers)Yi-Dong Shen (4 shared papers)Dongchun Ren (10 shared papers)Bo Zhang (6 shared papers)Di Wang (9 shared papers)Dacheng Tao (3 shared papers)
- Journals
- Neurocomputing (5 papers)Pattern Recognition (5 papers)IEEE Transactions on Neural Networks and Learning Systems (4 papers)IEEE Signal Processing Letters (3 papers)Information Sciences (2 papers)
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Mingyu Fan
63 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 118
- Computer Vision and Pattern Recognition 718
- Computational Mathematics 11
- Artificial Intelligence 570
- Media Technology 128
- Automotive Engineering 144
Countries citing papers authored by Mingyu Fan
This map shows the geographic impact of Mingyu Fan'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 Mingyu Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyu Fan more than expected).
Fields of papers citing papers by Mingyu Fan
This network shows the impact of papers produced by Mingyu Fan. 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 Mingyu Fan. The network helps show where Mingyu Fan may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingyu Fan, 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 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 129 | |
| 2 | Robust multiple kernel K-means using ℓ 2;1 -norm | 2015 | 123 |
| 3 | 2020 | 96 | |
| 4 | 2020 | 89 | |
| 5 | 2012 | 70 | |
| 6 | 2019 | 65 | |
| 7 | 2011 | 48 | |
| 8 | 2021 | 46 | |
| 9 | 2021 | 41 | |
| 10 | 2008 | 38 | |
| 11 | 2017 | 36 | |
| 12 | 2015 | 30 | |
| 13 | 2019 | 30 | |
| 14 | 2021 | 28 | |
| 15 | 2023 | 20 | |
| 16 | 2017 | 19 | |
| 17 | 2022 | 19 | |
| 18 | 2018 | 19 | |
| 19 | 2016 | 19 | |
| 20 | 2020 | 17 |
About Mingyu Fan
Mingyu Fan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Computational Mechanics and Media Technology, having authored 68 papers that have together received 1.3k indexed citations. Recurring topics across this work include Face and Expression Recognition (27 papers), Video Surveillance and Tracking Methods (14 papers), Autonomous Vehicle Technology and Safety (10 papers), Sparse and Compressive Sensing Techniques (8 papers), Advanced Image and Video Retrieval Techniques (8 papers), Anomaly Detection Techniques and Applications (6 papers), Remote-Sensing Image Classification (5 papers) and Robotic Path Planning Algorithms (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (718 citations), Computational Mathematics (11 citations), Artificial Intelligence (570 citations), Media Technology (128 citations) and Automotive Engineering (144 citations). Mingyu Fan has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Xiaoqin Zhang, Peng Zhou, Liang Du, Yi-Dong Shen, Dongchun Ren, Bo Zhang, Di Wang, Dacheng Tao, Xu Yang and Hao Zhou. Their work appears in journals such as Neurocomputing, Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems, IEEE Signal Processing Letters and Information Sciences.
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.