Kejun Wu
Impact in
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- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Media Technology top 10%
- Image Processing Techniques and Applications
- Advanced Image Fusion Techniques
Papers in
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- Advanced Image Processing Techniques 9
- Advanced Vision and Imaging 9
- Advanced Neural Network Applications 4
- Image Enhancement Techniques 4
- Video Surveillance and Tracking Methods 4
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- Image Processing Techniques and Applications 7
- Advanced Image Fusion Techniques 3
- Co-authors
- Chih‐Hsiang Ho (1 shared paper)You Yang (15 shared papers)M. W. Ackerman (1 shared paper)Qiong Liu (11 shared papers)Xiao–Ping Zhang (3 shared papers)Yi Wang (6 shared papers)Kim–Hui Yap (10 shared papers)Lap‐Pui Chau (6 shared papers)
In The Last Decade
Kejun Wu
34 papers receiving 282 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 103
- Media Technology 41
- Signal Processing 24
- Mechanical Engineering 61
- Materials Chemistry 64
Countries citing papers authored by Kejun Wu
This map shows the geographic impact of Kejun 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 Kejun Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kejun Wu more than expected).
Fields of papers citing papers by Kejun Wu
This network shows the impact of papers produced by Kejun 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 Kejun Wu. The network helps show where Kejun Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kejun 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 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1978 | 122 | |
| 2 | 2022 | 22 | |
| 3 | 2023 | 16 | |
| 4 | 2023 | 12 | |
| 5 | 2020 | 11 | |
| 6 | 2023 | 11 | |
| 7 | 2021 | 9 | |
| 8 | 2022 | 9 | |
| 9 | 2023 | 9 | |
| 10 | 2019 | 6 | |
| 11 | 2023 | 6 | |
| 12 | 2024 | 5 | |
| 13 | 2024 | 5 | |
| 14 | 2024 | 4 | |
| 15 | 2024 | 4 | |
| 16 | 2020 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2025 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2024 | 3 |
About Kejun Wu
Kejun Wu is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Signal Processing, Information Systems and Artificial Intelligence, having authored 41 papers that have together received 289 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (9 papers), Advanced Vision and Imaging (9 papers), Image Processing Techniques and Applications (7 papers), Advanced Neural Network Applications (4 papers), Image Enhancement Techniques (4 papers), Digital and Cyber Forensics (4 papers), Video Surveillance and Tracking Methods (4 papers) and Advanced Image Fusion Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (103 citations), Media Technology (41 citations), Signal Processing (24 citations), Mechanical Engineering (61 citations) and Materials Chemistry (64 citations). Kejun Wu has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Chih‐Hsiang Ho, You Yang, M. W. Ackerman, Qiong Liu, Xiao–Ping Zhang, Yi Wang, Kim–Hui Yap, Lap‐Pui Chau, Gangyi Jiang and Mei Yu. Their work appears in journals such as IEEE Transactions on Multimedia, ACM Transactions on Multimedia Computing Communications and Applications, Optics Express, Applied Intelligence and The Visual Computer.
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.