Mingjun Jiang
Impact in
- Media Technology top 5%
- Image Processing Techniques and Applications
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- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Optical measurement and interference techniques
- Advanced Neural Network Applications
Papers in
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- Advanced Vision and Imaging 9
- Optical measurement and interference techniques 7
- Video Surveillance and Tracking Methods 6
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- Image Processing Techniques and Applications 6
- Co-authors
- Idaku Ishii (18 shared papers)Kohei Shimasaki (16 shared papers)Shaopeng Hu (8 shared papers)Taku Senoo (5 shared papers)Takeshi Takaki (11 shared papers)Kazuhiko Yamamoto (3 shared papers)Xiaochuan Guo (1 shared paper)Yan He (1 shared paper)
In The Last Decade
Mingjun Jiang
37 papers receiving 297 citations
Peers
Comparison fields: 5 of 77
- Media Technology 60
- Computer Vision and Pattern Recognition 133
- Instrumentation 12
- Environmental Engineering 33
- Aerospace Engineering 42
Countries citing papers authored by Mingjun Jiang
This map shows the geographic impact of Mingjun Jiang'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 Mingjun Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingjun Jiang more than expected).
Fields of papers citing papers by Mingjun Jiang
This network shows the impact of papers produced by Mingjun Jiang. 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 Mingjun Jiang. The network helps show where Mingjun Jiang may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingjun Jiang, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 35 | |
| 2 | 2021 | 33 | |
| 3 | 2017 | 31 | |
| 4 | 2021 | 29 | |
| 5 | 2020 | 21 | |
| 6 | 2021 | 19 | |
| 7 | 2019 | 14 | |
| 8 | 2022 | 13 | |
| 9 | 2019 | 13 | |
| 10 | 2019 | 10 | |
| 11 | 2018 | 10 | |
| 12 | 2024 | 9 | |
| 13 | 2022 | 9 | |
| 14 | 2020 | 7 | |
| 15 | 2018 | 7 | |
| 16 | 2018 | 7 | |
| 17 | 2018 | 6 | |
| 18 | 2019 | 5 | |
| 19 | 2023 | 4 | |
| 20 | 2019 | 4 |
About Mingjun Jiang
Mingjun Jiang is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Aerospace Engineering, Ocean Engineering and Biophysics, having authored 38 papers that have together received 320 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (9 papers), Optical measurement and interference techniques (7 papers), Image Processing Techniques and Applications (6 papers), Video Surveillance and Tracking Methods (6 papers), Advanced Fluorescence Microscopy Techniques (4 papers), Robotics and Sensor-Based Localization (4 papers), Rock Mechanics and Modeling (3 papers) and Insect and Arachnid Ecology and Behavior (2 papers). The work is most often cited by research in Media Technology (60 citations), Computer Vision and Pattern Recognition (133 citations), Instrumentation (12 citations), Environmental Engineering (33 citations) and Aerospace Engineering (42 citations). Mingjun Jiang has collaborated with scholars based in China, Japan and Taiwan. Frequent co-authors include Idaku Ishii, Kohei Shimasaki, Shaopeng Hu, Taku Senoo, Takeshi Takaki, Kazuhiko Yamamoto, Xiaochuan Guo, Yan He, Pingkai Ouyang and Sheng Xu. Their work appears in journals such as IEEE Sensors Journal, IEEE Robotics and Automation Letters, IEEE Transactions on Instrumentation and Measurement, Journal of Polymer Research and Physics of Fluids.
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.