Chang‐Tsun Li
- Computer Vision and Pattern Recognition top 0.2%
- Artificial Intelligence top 2%
- Media Technology top 1%
- Biomedical Engineering top 10%
- Signal Processing top 2%
- Topics
- Digital Media Forensic Detection (92 papers)Advanced Steganography and Watermarking Techniques (78 papers)Chaos-based Image/Signal Encryption (31 papers)
- Partner nations
- United KingdomAustraliaChina
In The Last Decade
Chang‐Tsun Li
198 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 137
- Computer Vision and Pattern Recognition 2.7k
- Artificial Intelligence 628
- Media Technology 437
- Biomedical Engineering 365
- Signal Processing 315
Countries citing papers authored by Chang‐Tsun Li
This map shows the geographic impact of Chang‐Tsun 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 Chang‐Tsun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang‐Tsun Li more than expected).
Fields of papers citing papers by Chang‐Tsun Li
This network shows the impact of papers produced by Chang‐Tsun 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 Chang‐Tsun Li. The network helps show where Chang‐Tsun Li may publish in the future.
Co-authorship network of co-authors of Chang‐Tsun Li
This figure shows the co-authorship network connecting the top 25 collaborators of Chang‐Tsun Li. A scholar is included among the top collaborators of Chang‐Tsun 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 Chang‐Tsun Li. Chang‐Tsun 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 | 4 | |
| 6 | 7 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 5 | |
| 10 | 2 | |
| 11 | 11 | |
| 12 | 24 | |
| 13 | 4 | |
| 14 | 34 | |
| 15 | 20 | |
| 16 | Digital Forensic Readiness: Are We There Yet? | 17 |
| 17 | 12 | |
| 18 | On the Repudiability of Device Identification and Image Integrity Verification Using Sensor Pattern Noise | 1 |
| 19 | Hand posture recognition using SURF with adaptive boosting | 6 |
| 20 | 30 |
About Chang‐Tsun Li
Chang‐Tsun Li is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Human-Computer Interaction, having authored 206 papers that have together received 3.2k indexed citations. Recurring topics across this work include Digital Media Forensic Detection (92 papers), Advanced Steganography and Watermarking Techniques (78 papers) and Chaos-based Image/Signal Encryption (31 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.7k citations), Media Technology (437 citations) and Signal Processing (315 citations). Chang‐Tsun Li has collaborated with scholars based in United Kingdom, Australia and China. Frequent co-authors include Víctor Sánchez, Xufeng Lin, Yu Guan, Yongjian Hu, Chia‐Hung Wei, Yue Li, Ching‐Chun Chang, R. Wilson, Fabio Roli and Xingjie Wei. Their work appears in journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.