Kun Fu
Impact in
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Media Technology top 5%
- Vehicle License Plate Recognition
Papers in
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- Multimodal Machine Learning Applications 3
- Image and Video Quality Assessment 2
- Human Pose and Action Recognition 2
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- Peer-to-Peer Network Technologies 4
- Network Traffic and Congestion Control 3
- Advanced Data Storage Technologies 2
- Co-authors
- Changshui Zhang (6 shared papers)Junqi Jin (3 shared papers)Fei Sha (1 shared paper)Runpeng Cui (1 shared paper)Roger Zimmermann (5 shared papers)R. D. Vispute (1 shared paper)Chunyan Zhang (1 shared paper)Chaoying Ni (1 shared paper)
- Journals
- IEEE Transactions on Intelligent Transportation Systems (3 papers)Journal of Materials Science (1 paper)Software Practice and Experience (1 paper)Multimedia Tools and Applications (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Kun Fu
13 papers receiving 450 citations
Peers
Comparison fields: 5 of 80
- Computer Vision and Pattern Recognition 310
- Media Technology 107
- Human-Computer Interaction 42
- Transportation 25
- Building and Construction 42
Countries citing papers authored by Kun Fu
This map shows the geographic impact of Kun Fu'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 Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Fu more than expected).
Fields of papers citing papers by Kun Fu
This network shows the impact of papers produced by Kun Fu. 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 Fu. The network helps show where Kun Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Fu, 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 | 2014 | 230 | |
| 2 | 2016 | 125 | |
| 3 | 2023 | 26 | |
| 4 | 2020 | 22 | |
| 5 | 2018 | 19 | |
| 6 | 2003 | 14 | |
| 7 | 2001 | 11 | |
| 8 | 2003 | 8 | |
| 9 | 2022 | 7 | |
| 10 | 2022 | 5 | |
| 11 | 2006 | 2 | |
| 12 | 2019 | 2 | |
| 13 | 2003 | 1 | |
| 14 | 2004 | 1 | |
| 15 | 2025 | 0 |
About Kun Fu
Kun Fu is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Molecular Biology, Sociology and Political Science and Transportation, having authored 15 papers that have together received 473 indexed citations. Recurring topics across this work include Peer-to-Peer Network Technologies (4 papers), Multimodal Machine Learning Applications (3 papers), Network Traffic and Congestion Control (3 papers), Advanced Data Storage Technologies (2 papers), Multimedia Communication and Technology (2 papers), Image and Video Quality Assessment (2 papers), Human Pose and Action Recognition (2 papers) and Human Mobility and Location-Based Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (310 citations), Media Technology (107 citations), Human-Computer Interaction (42 citations), Transportation (25 citations) and Building and Construction (42 citations). Kun Fu has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Changshui Zhang, Junqi Jin, Fei Sha, Runpeng Cui, Roger Zimmermann, R. D. Vispute, Chunyan Zhang, Chaoying Ni, Jin Li and Donghua Zhou. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Journal of Materials Science, Software Practice and Experience, Multimedia Tools and Applications and IEEE Transactions on Neural Networks and Learning Systems.
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.