P. Mathivanan
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Signal Processing
- Computational Theory and Mathematics
- Statistical and Nonlinear Physics
- Co-authors
- A. Balaji GaneshPalaniappan RamuS. Edward JeroRamarathnam VenkatesanSajjad Shaukat JamalK. MahalakshmiK. VenkatasubramanianAceng Sambas
- Topics
- Advanced Steganography and Watermarking Techniques (16 papers)Chaos-based Image/Signal Encryption (11 papers)Biometric Identification and Security (4 papers)
- Partner nations
- IndiaSaudi ArabiaMalaysia
In The Last Decade
P. Mathivanan
22 papers receiving 230 citations
Peers
Comparison fields: 5 of 45
- Computer Vision and Pattern Recognition 195
- Artificial Intelligence 41
- Signal Processing 24
- Computational Theory and Mathematics 24
- Statistical and Nonlinear Physics 22
Countries citing papers authored by P. Mathivanan
This map shows the geographic impact of P. Mathivanan'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 P. Mathivanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. Mathivanan more than expected).
Fields of papers citing papers by P. Mathivanan
This network shows the impact of papers produced by P. Mathivanan. 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 P. Mathivanan. The network helps show where P. Mathivanan may publish in the future.
Co-authorship network of co-authors of P. Mathivanan
This figure shows the co-authorship network connecting the top 25 collaborators of P. Mathivanan. A scholar is included among the top collaborators of P. Mathivanan 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 P. Mathivanan. P. Mathivanan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 4 | |
| 10 | 19 | |
| 11 | 0 | |
| 12 | 1 | |
| 13 | 16 | |
| 14 | 1 | |
| 15 | 18 | |
| 16 | 23 | |
| 17 | 25 | |
| 18 | 2 | |
| 19 | 10 | |
| 20 | Conversion of 2D Stegano Images into a 3D Stereo Image using RANSAC | 1 |
About P. Mathivanan
P. Mathivanan is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Neurology, having authored 30 papers that have together received 244 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (16 papers), Chaos-based Image/Signal Encryption (11 papers) and Biometric Identification and Security (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (195 citations), Signal Processing (24 citations) and Statistical and Nonlinear Physics (22 citations). P. Mathivanan has collaborated with scholars based in India, Saudi Arabia and Malaysia. Frequent co-authors include A. Balaji Ganesh, Palaniappan Ramu, S. Edward Jero, Ramarathnam Venkatesan, Sajjad Shaukat Jamal, K. Mahalakshmi, K. Venkatasubramanian and Aceng Sambas. Their work appears in journals such as Nonlinear Dynamics, Multimedia Tools and Applications and Optik.
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.