Xiaofeng Cong
Impact in
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- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Advanced Neural Network Applications
- Generative Adversarial Networks and Image Synthesis
- Media Technology top 10%
- Advanced Image Fusion Techniques
Papers in
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- Image Enhancement Techniques 11
- Advanced Image Processing Techniques 1
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- Advanced Image Fusion Techniques 6
- Co-authors
- Jie Gui (10 shared papers)Junming Hou (8 shared papers)Jing Zhang (2 shared papers)Dacheng Tao (4 shared papers)Yuan Cao (2 shared papers)Jun Zhang (2 shared papers)Wenqi Ren (2 shared papers)Hao Shen (1 shared paper)
In The Last Decade
Xiaofeng Cong
19 papers receiving 296 citations
Peers
Comparison fields: 5 of 14
- Computer Vision and Pattern Recognition 263
- Media Technology 32
- Acoustics and Ultrasonics 1
- Signal Processing 4
- Artificial Intelligence 14
Countries citing papers authored by Xiaofeng Cong
This map shows the geographic impact of Xiaofeng Cong'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 Xiaofeng Cong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaofeng Cong more than expected).
Fields of papers citing papers by Xiaofeng Cong
This network shows the impact of papers produced by Xiaofeng Cong. 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 Xiaofeng Cong. The network helps show where Xiaofeng Cong may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaofeng Cong, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 67 | |
| 2 | 2024 | 44 | |
| 3 | 2021 | 35 | |
| 4 | 2020 | 31 | |
| 5 | 2020 | 22 | |
| 6 | 2023 | 17 | |
| 7 | 2024 | 17 | |
| 8 | 2023 | 15 | |
| 9 | 2024 | 13 | |
| 10 | 2024 | 12 | |
| 11 | 2024 | 12 | |
| 12 | 2023 | 7 | |
| 13 | 2025 | 5 | |
| 14 | 2025 | 3 | |
| 15 | 2025 | 3 | |
| 16 | 2026 | 3 | |
| 17 | 2026 | 2 | |
| 18 | 2020 | 1 | |
| 19 | 2025 | 1 | |
| 20 | 2020 | 0 |
About Xiaofeng Cong
Xiaofeng Cong is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Computational Mechanics and Nuclear Energy and Engineering, having authored 21 papers that have together received 310 indexed citations. Recurring topics across this work include Image Enhancement Techniques (11 papers), Advanced Image Fusion Techniques (6 papers), Adversarial Robustness in Machine Learning (2 papers), Advanced Image Processing Techniques (1 paper) and 3D Shape Modeling and Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (263 citations), Media Technology (32 citations), Acoustics and Ultrasonics (1 citation), Signal Processing (4 citations) and Artificial Intelligence (14 citations). Xiaofeng Cong has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Jie Gui, Junming Hou, Jing Zhang, Dacheng Tao, Yuan Cao, Jun Zhang, Wenqi Ren, Hao Shen, James Tin-Yau Kwok and Yuan Yan Tang. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Information Fusion, International Journal of Computer Vision, ACM Computing Surveys and IEEE Transactions on Emerging Topics in Computational Intelligence.
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.