Canyi Lu
Impact in
- Computational Mathematics top 0.05%
- Tensor decomposition and applications
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- Face and Expression Recognition
- Image and Signal Denoising Methods
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
Papers in
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- Tensor decomposition and applications 5
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- Face and Expression Recognition 13
- Advanced Image and Video Retrieval Techniques 5
- Image and Signal Denoising Methods 4
- Face recognition and analysis 3
- Journals
- IEEE Transactions on Circuits and Systems for Video Technology (4 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (4 papers)IEEE Transactions on Cybernetics (2 papers)IEEE Transactions on Image Processing (2 papers)Machine Learning (2 papers)
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Canyi Lu
33 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Computational Mathematics 986
- Computer Vision and Pattern Recognition 2.3k
- Computational Mechanics 1.7k
- Media Technology 659
- Signal Processing 460
Countries citing papers authored by Canyi Lu
This map shows the geographic impact of Canyi Lu'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 Canyi Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Canyi Lu more than expected).
Fields of papers citing papers by Canyi Lu
This network shows the impact of papers produced by Canyi Lu. 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 Canyi Lu. The network helps show where Canyi Lu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Canyi Lu, 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 | 2023 | 14 | |
| 2 | 2023 | 11 | |
| 3 | 2023 | 10 | |
| 4 | 2021 | 23 | |
| 5 | 2019 | 113 | |
| 6 | 2018 | 34 | |
| 7 | 2016 | 3 | |
| 8 | 2016 | 281 | |
| 9 | 2016 | 145 | |
| 10 | Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization Hit paper breakdown → | 2016 | 394 |
| 11 | 2016 | 7 | |
| 12 | 2015 | 72 | |
| 13 | 2015 | 134 | |
| 14 | 2014 | 209 | |
| 15 | 2014 | 178 | |
| 16 | 2014 | 11 | |
| 17 | 2013 | 75 | |
| 18 | 2013 | 16 | |
| 19 | 2013 | 56 | |
| 20 | 2012 | 177 |
About Canyi Lu
Canyi Lu is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Computational Mechanics, Signal Processing and Media Technology, having authored 33 papers that have together received 3.8k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (21 papers), Face and Expression Recognition (13 papers), Blind Source Separation Techniques (6 papers), Tensor decomposition and applications (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Image and Signal Denoising Methods (4 papers), Remote-Sensing Image Classification (4 papers) and Face recognition and analysis (3 papers). The work is most often cited by research in Computational Mathematics (986 citations), Computer Vision and Pattern Recognition (2.3k citations), Computational Mechanics (1.7k citations), Media Technology (659 citations) and Signal Processing (460 citations). Canyi Lu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Shuicheng Yan, Zhouchen Lin, Jiashi Feng, Yudong Chen, Wei Liu, Yunchao Wei, Pan Zhou, Tao Mei, Jinhui Tang and Chao Zhang. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Cybernetics, IEEE Transactions on Image Processing and Machine Learning.
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.