Feifan Lv
Impact in
- Media Technology top 2%
- Advanced Image Fusion Techniques
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- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Advanced Vision and Imaging
- Image and Signal Denoising Methods
- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Image and Video Quality Assessment
Papers in
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- Image Enhancement Techniques 5
- Advanced Image Processing Techniques 4
- Advanced Vision and Imaging 1
- Image and Signal Denoising Methods 1
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- Advanced Image Fusion Techniques 3
- Image Processing Techniques and Applications 1
- Co-authors
- Feng Lu (5 shared papers)Yu Li (1 shared paper)Jian Wu (1 shared paper)Feng Lu (1 shared paper)Bo Liu (1 shared paper)Yinqiang Zheng (2 shared papers)Yicheng Li (1 shared paper)Bohan Zhang (1 shared paper)
- Journals
- International Journal of Computer Vision (1 paper)British Machine Vision Conference (1 paper)arXiv (Cornell University) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Feifan Lv
6 papers receiving 495 citations
Feifan Lv's Hit Papers
Peers
Comparison fields: 5 of 47
- Media Technology 222
- Computer Vision and Pattern Recognition 478
- Acoustics and Ultrasonics 5
- Instrumentation 9
- Geology 6
Countries citing papers authored by Feifan Lv
This map shows the geographic impact of Feifan Lv'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 Feifan Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feifan Lv more than expected).
Fields of papers citing papers by Feifan Lv
This network shows the impact of papers produced by Feifan Lv. 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 Feifan Lv. The network helps show where Feifan Lv may publish in the future.
Co-authors
The 8 scholars most cited alongside Feifan Lv, 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 | MBLLEN: Low-Light Image/Video Enhancement Using CNNs. | 2018 | 227 |
| 2 | Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset Hit paper breakdown → | 2021 | 206 |
| 3 | 2020 | 44 | |
| 4 | Attention-guided Low-light Image Enhancement. | 2019 | 14 |
| 5 | 2020 | 12 | |
| 6 | 2019 | 4 |
About Feifan Lv
Feifan Lv is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Aerospace Engineering, Electrical and Electronic Engineering and Infectious Diseases, having authored 6 papers that have together received 507 indexed citations. Recurring topics across this work include Image Enhancement Techniques (5 papers), Advanced Image Processing Techniques (4 papers), Advanced Image Fusion Techniques (3 papers), Infrared Target Detection Methodologies (2 papers), Image Processing Techniques and Applications (1 paper), CCD and CMOS Imaging Sensors (1 paper), Advanced Vision and Imaging (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Media Technology (222 citations), Computer Vision and Pattern Recognition (478 citations), Acoustics and Ultrasonics (5 citations), Instrumentation (9 citations) and Geology (6 citations). Feifan Lv has collaborated with scholars based in China and Japan. Frequent co-authors include Feng Lu, Yu Li, Jian Wu, Feng Lu, Bo Liu, Yinqiang Zheng, Yicheng Li and Bohan Zhang. Their work appears in journals such as International Journal of Computer Vision, British Machine Vision Conference, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial 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.