Kun Dai
Impact in
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- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Robotic Path Planning Algorithms
- Aerospace Engineering top 10%
- Robotics and Sensor-Based Localization
Papers in
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- Advanced Image and Video Retrieval Techniques 19
- Advanced Neural Network Applications 13
- Advanced Vision and Imaging 7
- Robotic Path Planning Algorithms 3
- Human Pose and Action Recognition 2
- Visual Attention and Saliency Detection 2
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- Robotics and Sensor-Based Localization 16
- Co-authors
- Ruifeng Li (26 shared papers)Ke Wang (25 shared papers)Lijun Zhao (18 shared papers)Tao Xie (18 shared papers)Zhiqiang Jiang (16 shared papers)Xiaoyu Li (2 shared papers)Tao Xie (3 shared papers)Eric Ke Wang (2 shared papers)
In The Last Decade
Kun Dai
33 papers receiving 216 citations
Peers
Comparison fields: 5 of 43
- Computer Vision and Pattern Recognition 152
- Aerospace Engineering 95
- Geology 14
- Media Technology 8
- Artificial Intelligence 22
Countries citing papers authored by Kun Dai
This map shows the geographic impact of Kun Dai'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 Kun Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Dai more than expected).
Fields of papers citing papers by Kun Dai
This network shows the impact of papers produced by Kun Dai. 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 Kun Dai. The network helps show where Kun Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Dai, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 39 | |
| 2 | 2023 | 27 | |
| 3 | 2022 | 18 | |
| 4 | 2023 | 16 | |
| 5 | 2023 | 14 | |
| 6 | 2023 | 13 | |
| 7 | 2023 | 9 | |
| 8 | 2024 | 8 | |
| 9 | 2023 | 7 | |
| 10 | 2021 | 7 | |
| 11 | 2023 | 7 | |
| 12 | 2024 | 6 | |
| 13 | 2024 | 5 | |
| 14 | 2024 | 5 | |
| 15 | 2023 | 5 | |
| 16 | 2024 | 4 | |
| 17 | 2023 | 4 | |
| 18 | 2023 | 4 | |
| 19 | 2014 | 4 | |
| 20 | 2022 | 2 |
About Kun Dai
Kun Dai is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Control and Systems Engineering, Computational Mechanics and Artificial Intelligence, having authored 37 papers that have together received 218 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (19 papers), Robotics and Sensor-Based Localization (16 papers), Advanced Neural Network Applications (13 papers), Advanced Vision and Imaging (7 papers), Robotic Path Planning Algorithms (3 papers), 3D Shape Modeling and Analysis (3 papers), Human Pose and Action Recognition (2 papers) and Visual Attention and Saliency Detection (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (152 citations), Aerospace Engineering (95 citations), Geology (14 citations), Media Technology (8 citations) and Artificial Intelligence (22 citations). Kun Dai has collaborated with scholars based in China, Egypt and Germany. Frequent co-authors include Ruifeng Li, Ke Wang, Lijun Zhao, Tao Xie, Zhiqiang Jiang, Xiaoyu Li, Tao Xie, Eric Ke Wang, Xinyue Tang and Jiahe Wang. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Expert Systems with Applications, IEEE Robotics and Automation Letters, IEEE Transactions on Multimedia and IEEE Transactions on Automation 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.