Xiaoping Liu
Impact in
- Applied Mathematics top 2%
- Mathematical Analysis and Transform Methods
- Signal Processing top 5%
- Digital Filter Design and Implementation
Papers in
-
- Image and Signal Denoising Methods 13
- Advanced Image Processing Techniques 1
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- Mathematical Analysis and Transform Methods 12
- Co-authors
- Jun Shi (13 shared papers)Naitong Zhang (8 shared papers)Qinyu Zhang (5 shared papers)Wei Xiang (5 shared papers)Xiaochen Sun (1 shared paper)Yulin Chen (1 shared paper)Ming‐Hui Lu (1 shared paper)Cheng He (1 shared paper)
- Journals
- IEEE Transactions on Signal Processing (8 papers)Signal Processing (2 papers)Proceedings of the National Academy of Sciences (1 paper)Digital Signal Processing (1 paper)Signal Image and Video Processing (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Xiaoping Liu
14 papers receiving 670 citations
Peers
Comparison fields: 5 of 48
- Applied Mathematics 324
- Signal Processing 242
- Computer Vision and Pattern Recognition 376
- Atomic and Molecular Physics, and Optics 197
- Acoustics and Ultrasonics 5
Countries citing papers authored by Xiaoping Liu
This map shows the geographic impact of Xiaoping Liu'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 Xiaoping Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoping Liu more than expected).
Fields of papers citing papers by Xiaoping Liu
This network shows the impact of papers produced by Xiaoping Liu. 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 Xiaoping Liu. The network helps show where Xiaoping Liu may publish in the future.
Co-authors
The 18 scholars most cited alongside Xiaoping Liu, 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 | 2016 | 207 | |
| 2 | 2020 | 76 | |
| 3 | 2012 | 67 | |
| 4 | 2012 | 52 | |
| 5 | 2016 | 46 | |
| 6 | 2018 | 42 | |
| 7 | 2021 | 31 | |
| 8 | 2018 | 31 | |
| 9 | 2020 | 30 | |
| 10 | 2017 | 30 | |
| 11 | 2012 | 27 | |
| 12 | 2013 | 20 | |
| 13 | 2013 | 19 | |
| 14 | 2014 | 8 |
About Xiaoping Liu
Xiaoping Liu is a scholar working on Computer Vision and Pattern Recognition, Applied Mathematics, Signal Processing, Molecular Biology and Atomic and Molecular Physics, and Optics, having authored 14 papers that have together received 686 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (13 papers), Mathematical Analysis and Transform Methods (12 papers), Digital Filter Design and Implementation (10 papers), Topological Materials and Phenomena (1 paper), Fractal and DNA sequence analysis (1 paper), Photonic Crystals and Applications (1 paper), Advanced Numerical Analysis Techniques (1 paper) and Advanced Image Processing Techniques (1 paper). The work is most often cited by research in Applied Mathematics (324 citations), Signal Processing (242 citations), Computer Vision and Pattern Recognition (376 citations), Atomic and Molecular Physics, and Optics (197 citations) and Acoustics and Ultrasonics (5 citations). Xiaoping Liu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jun Shi, Naitong Zhang, Qinyu Zhang, Wei Xiang, Xiaochen Sun, Yulin Chen, Ming‐Hui Lu, Cheng He, Yan‐Feng Chen and Xuejun Sha. Their work appears in journals such as IEEE Transactions on Signal Processing, Signal Processing, Proceedings of the National Academy of Sciences, Digital Signal Processing and Signal Image and Video Processing.
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.