Yiqun Mei
- Computer Vision and Pattern Recognition top 1%
- Media Technology top 0.5%
- Radiology, Nuclear Medicine and Imaging
- Biomedical Engineering
- Artificial Intelligence
- Co-authors
- Yuchen FanYuqian ZhouThomas S. HuangHumphrey ShiLichao HuangVishal M. PatelPengfei GuoShanshan Jiang
- Topics
- Advanced Image Processing Techniques (6 papers)Advanced Vision and Imaging (5 papers)Image Processing Techniques and Applications (3 papers)
- Cited by
- Media TechnologyComputer Vision and Pattern RecognitionComputer Graphics and Computer-Aided Design
- Journals
- IEEE Transactions on Medical ImagingInternational Journal of Computer Vision2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United StatesSwitzerland
In The Last Decade
Yiqun Mei
10 papers receiving 787 citations
Hit Papers
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 703
- Media Technology 445
- Radiology, Nuclear Medicine and Imaging 57
- Biomedical Engineering 51
- Artificial Intelligence 20
Countries citing papers authored by Yiqun Mei
This map shows the geographic impact of Yiqun Mei'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 Yiqun Mei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yiqun Mei more than expected).
Fields of papers citing papers by Yiqun Mei
This network shows the impact of papers produced by Yiqun Mei. 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 Yiqun Mei. The network helps show where Yiqun Mei may publish in the future.
Co-authorship network of co-authors of Yiqun Mei
This figure shows the co-authorship network connecting the top 25 collaborators of Yiqun Mei. A scholar is included among the top collaborators of Yiqun Mei based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yiqun Mei. Yiqun Mei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 49 | |
| 6 | 58 | |
| 7 | 7 | |
| 8 | 4 | |
| 9 | 8 | |
| 10 | Image Super-Resolution with Non-Local Sparse Attentionbreakdown → | 383 |
| 11 | Image Super-Resolution With Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Miningbreakdown → | 278 |
| 12 | 4 |
About Yiqun Mei
Yiqun Mei is a scholar working on Computer Graphics and Computer-Aided Design, Media Technology and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 795 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (6 papers), Advanced Vision and Imaging (5 papers) and Image Processing Techniques and Applications (3 papers). The work is most often cited by research in Media Technology (445 citations), Computer Vision and Pattern Recognition (703 citations) and Computer Graphics and Computer-Aided Design (16 citations). Yiqun Mei has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Yuchen Fan, Yuqian Zhou, Thomas S. Huang, Humphrey Shi, Lichao Huang, Vishal M. Patel, Pengfei Guo, Shanshan Jiang, Jinyuan Zhou and Yun Fu. Their work appears in journals such as IEEE Transactions on Medical Imaging, International Journal of Computer Vision and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.