Xiongfei Li
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 0.5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging
- Topics
- Advanced Image Fusion Techniques (36 papers)Image and Signal Denoising Methods (17 papers)Image Enhancement Techniques (15 papers)
- Journals
- BioinformaticsACS Applied Materials & InterfacesIEEE Transactions on Geoscience and Remote Sensing
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Xiongfei Li
94 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 136
- Computer Vision and Pattern Recognition 576
- Media Technology 502
- Artificial Intelligence 187
- Biomedical Engineering 167
- Radiology, Nuclear Medicine and Imaging 89
Countries citing papers authored by Xiongfei Li
This map shows the geographic impact of Xiongfei Li'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 Xiongfei Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiongfei Li more than expected).
Fields of papers citing papers by Xiongfei Li
This network shows the impact of papers produced by Xiongfei Li. 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 Xiongfei Li. The network helps show where Xiongfei Li may publish in the future.
Co-authorship network of co-authors of Xiongfei Li
This figure shows the co-authorship network connecting the top 25 collaborators of Xiongfei Li. A scholar is included among the top collaborators of Xiongfei Li 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 Xiongfei Li. Xiongfei Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 12 | |
| 8 | 15 | |
| 9 | 1 | |
| 10 | 18 | |
| 11 | 8 | |
| 12 | 7 | |
| 13 | 18 | |
| 14 | 11 | |
| 15 | 4 | |
| 16 | 69 | |
| 17 | Imbalanced Data Classification Algorithm Based on Undersampling | 0 |
| 18 | Research and design of drawings retrieval system based on content | 0 |
| 19 | Parallel algorithm of attribute reduction in rough set | 0 |
| 20 | 1 |
About Xiongfei Li
Xiongfei Li is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 107 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (36 papers), Image and Signal Denoising Methods (17 papers) and Image Enhancement Techniques (15 papers). The work is most often cited by research in Media Technology (502 citations), Computer Vision and Pattern Recognition (576 citations) and Neurology (73 citations). Xiongfei Li has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Xiaoli Zhang, Yuncong Feng, Zeyu Wang, Haoran Duan, Rui Zhu, Haiying Zhao, Zhaojun Liu, Hancheng Wang, Shuang Yu and Xiaohan Hu. Their work appears in journals such as Bioinformatics, ACS Applied Materials & Interfaces and IEEE Transactions on Geoscience and Remote Sensing.
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.