Prashant Narayankar
Impact in
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- Chaos-based Image/Signal Encryption
- Advanced Steganography and Watermarking Techniques
- Artificial Intelligence top 10%
- Cryptographic Implementations and Security
- Cryptography and Data Security
- Coding theory and cryptography
Papers in
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- Cloud Computing and Resource Management 1
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- Video Surveillance and Tracking Methods 1
- Human Pose and Action Recognition 1
- Co-authors
- Priyadarshini Patil (2 shared papers)Meena S.M. (1 shared paper)D. G. Narayan (1 shared paper)M. Vijayalakshmi (2 shared papers)Padmashree Desai (2 shared papers)Meenaxi M Raikar (2 shared papers)Vishwanath P. Baligar (2 shared papers)
- Journals
- Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation (1 paper)Lecture notes in networks and systems (1 paper)Procedia Computer Science (1 paper)
- Partner nations
- India
In The Last Decade
Prashant Narayankar
7 papers receiving 257 citations
Peers
Comparison fields: 5 of 42
- Computer Vision and Pattern Recognition 142
- Artificial Intelligence 140
- Signal Processing 37
- Information Systems 76
- Computer Networks and Communications 67
Countries citing papers authored by Prashant Narayankar
This map shows the geographic impact of Prashant Narayankar'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 Prashant Narayankar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prashant Narayankar more than expected).
Fields of papers citing papers by Prashant Narayankar
This network shows the impact of papers produced by Prashant Narayankar. 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 Prashant Narayankar. The network helps show where Prashant Narayankar may publish in the future.
Co-authors
The 7 scholars most cited alongside Prashant Narayankar, 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 | 232 | |
| 2 | 2018 | 18 | |
| 3 | 2016 | 13 | |
| 4 | 2018 | 8 | |
| 5 | 2024 | 6 | |
| 6 | 2016 | 1 | |
| 7 | 2021 | 1 |
About Prashant Narayankar
Prashant Narayankar is a scholar working on Information Systems, Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Management Information Systems, having authored 7 papers that have together received 279 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (1 paper), Cloud Computing and Resource Management (1 paper), Advanced Malware Detection Techniques (1 paper), Glaucoma and retinal disorders (1 paper), Technology Adoption and User Behaviour (1 paper), Big Data and Business Intelligence (1 paper), Brain Tumor Detection and Classification (1 paper) and Human Pose and Action Recognition (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (142 citations), Artificial Intelligence (140 citations), Signal Processing (37 citations), Information Systems (76 citations) and Computer Networks and Communications (67 citations). Prashant Narayankar has collaborated with scholars based in India. Frequent co-authors include Priyadarshini Patil, Meena S.M., D. G. Narayan, M. Vijayalakshmi, Padmashree Desai, Meenaxi M Raikar and Vishwanath P. Baligar. Their work appears in journals such as Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation, Lecture notes in networks and systems and Procedia Computer Science.
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.