Kan Li
Impact in
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- Advanced Steganography and Watermarking Techniques
- Chaos-based Image/Signal Encryption
- Digital Media Forensic Detection
- Signal Processing top 10%
- Speech and Audio Processing
- Blind Source Separation Techniques
Papers in
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- Neural Networks and Applications 6
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- Advanced Steganography and Watermarking Techniques 3
- Co-authors
- Xiao–Ping Zhang (3 shared papers)José C. Prı́ncipe (13 shared papers)Haiquan Zhao (1 shared paper)Badong Chen (2 shared papers)Lu Lu (1 shared paper)William W. Lytton (3 shared papers)Shujian Yu (1 shared paper)Xiaofeng Wang (1 shared paper)
- Journals
- Journal of Cardiac Failure (2 papers)Computers and Electronics in Agriculture (2 papers)Frontiers in Neuroscience (2 papers)Animals (1 paper)ETRI Journal (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Kan Li
51 papers receiving 521 citations
Peers
Comparison fields: 5 of 117
- Computer Vision and Pattern Recognition 205
- Signal Processing 74
- Computational Mechanics 64
- Artificial Intelligence 78
- Media Technology 18
Countries citing papers authored by Kan Li
This map shows the geographic impact of Kan 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 Kan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kan Li more than expected).
Fields of papers citing papers by Kan Li
This network shows the impact of papers produced by Kan 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 Kan Li. The network helps show where Kan Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Kan Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 135 | |
| 2 | 2017 | 40 | |
| 3 | 2016 | 37 | |
| 4 | 2017 | 28 | |
| 5 | 2016 | 28 | |
| 6 | 2015 | 26 | |
| 7 | 2016 | 26 | |
| 8 | 2015 | 25 | |
| 9 | 2016 | 24 | |
| 10 | 2024 | 22 | |
| 11 | 2023 | 16 | |
| 12 | 2008 | 14 | |
| 13 | 2024 | 11 | |
| 14 | 2018 | 8 | |
| 15 | 2018 | 7 | |
| 16 | 2025 | 7 | |
| 17 | 2021 | 6 | |
| 18 | 2023 | 6 | |
| 19 | 2024 | 6 | |
| 20 | 2023 | 5 |
About Kan Li
Kan Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Electrical and Electronic Engineering and Biomedical Engineering, having authored 53 papers that have together received 539 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), Advanced Adaptive Filtering Techniques (5 papers), Blind Source Separation Techniques (4 papers), EEG and Brain-Computer Interfaces (4 papers), Speech and Audio Processing (4 papers), Advanced Memory and Neural Computing (3 papers), Advanced Steganography and Watermarking Techniques (3 papers) and Advanced Algorithms and Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (205 citations), Signal Processing (74 citations), Computational Mechanics (64 citations), Artificial Intelligence (78 citations) and Media Technology (18 citations). Kan Li has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Xiao–Ping Zhang, José C. Prı́ncipe, Haiquan Zhao, Badong Chen, Lu Lu, William W. Lytton, Shujian Yu, Xiaofeng Wang, Salvador Durá-Bernal and Xinge You. Their work appears in journals such as Journal of Cardiac Failure, Computers and Electronics in Agriculture, Frontiers in Neuroscience, Animals and ETRI Journal.
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.