Mingkui Tan
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- Multimodal Machine Learning Applications 31
- Advanced Neural Network Applications 25
- Human Pose and Action Recognition 22
- Advanced Image and Video Retrieval Techniques 22
- Face and Expression Recognition 13
- Advanced Vision and Imaging 11
- Media Technology top 0.2%
- Artificial Intelligence top 0.2%
- Domain Adaptation and Few-Shot Learning 43
- Computational Mathematics top 2%
- Human-Computer Interaction top 2%
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- Sparse and Compressive Sensing Techniques 15
Mingkui Tan
145 papers receiving 7.9k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Computer Vision and Pattern Recognition 5.4k
- Media Technology 917
- Artificial Intelligence 3.3k
- Computational Mathematics 43
- Human-Computer Interaction 209
Countries citing papers authored by Mingkui Tan
This map shows the geographic impact of Mingkui Tan'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 Mingkui Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingkui Tan more than expected).
Fields of papers citing papers by Mingkui Tan
This network shows the impact of papers produced by Mingkui Tan. 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 Mingkui Tan. The network helps show where Mingkui Tan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mingkui Tan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 7 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 24 | |
| 10 | 2023 | 4 | |
| 11 | 2023 | 5 | |
| 12 | 2023 | 5 | |
| 13 | 2021 | 6 | |
| 14 | 2021 | 64 | |
| 15 | 2021 | 27 | |
| 16 | 2020 | 50 | |
| 17 | 2019 | 56 | |
| 18 | 2019 | 6 | |
| 19 | 2018 | 31 | |
| 20 | 2018 | 4 |
About Mingkui Tan
Mingkui Tan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mathematics, having authored 151 papers that have together received 8.1k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (43 papers), Multimodal Machine Learning Applications (31 papers), Advanced Neural Network Applications (25 papers), Human Pose and Action Recognition (22 papers), Advanced Image and Video Retrieval Techniques (22 papers), Sparse and Compressive Sensing Techniques (15 papers), Face and Expression Recognition (13 papers) and Advanced Vision and Imaging (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.4k citations), Media Technology (917 citations) and Artificial Intelligence (3.3k citations). Mingkui Tan has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Jingdong Wang, Chaorui Deng, Ke Sun, Borui Jiang, Tianheng Cheng, Bin Xiao, Yang Zhao, Dong Liu, Yadong Mu and Xinggang Wang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Multimedia, IEEE Transactions on Image Processing and IEEE Transactions on Circuits and Systems for Video Technology.
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.