S. Premkumar
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- IoT and Edge/Fog Computing 4
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- Blockchain Technology Applications and Security 3
- Cloud Computing and Resource Management 3
- Advanced Technology in Applications 1
- Co-authors
- S. Velliangiri (1 shared paper)Vani Rajasekar (1 shared paper)Arun Narayanan (1 shared paper)Dankan Gowda (2 shared papers)M. A. Gopinath (1 shared paper)Naziya Hussain (1 shared paper)KDV Prasad (1 shared paper)Lalitha Subramanian (1 shared paper)
- Journals
- Knowledge-Based Systems (1 paper)Results in Engineering (1 paper)Network Computation in Neural Systems (1 paper)Journal of Water Process Engineering (1 paper)Computational Intelligence (1 paper)
- Partner nations
- India
In The Last Decade
S. Premkumar
13 papers receiving 171 citations
Peers
Comparison fields: 5 of 42
- Radiology, Nuclear Medicine and Imaging 59
- Health Information Management 10
- Computer Vision and Pattern Recognition 41
- Computer Networks and Communications 34
- Neurology 11
Countries citing papers authored by S. Premkumar
This map shows the geographic impact of S. Premkumar'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 S. Premkumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Premkumar more than expected).
Fields of papers citing papers by S. Premkumar
This network shows the impact of papers produced by S. Premkumar. 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 S. Premkumar. The network helps show where S. Premkumar may publish in the future.
Co-authors
The 10 scholars most cited alongside S. Premkumar, 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 | 84 | |
| 2 | 2022 | 19 | |
| 3 | 2023 | 18 | |
| 4 | 2023 | 13 | |
| 5 | 2018 | 12 | |
| 6 | 2012 | 12 | |
| 7 | 2014 | 10 | |
| 8 | 2025 | 5 | |
| 9 | 2019 | 5 | |
| 10 | 2018 | 5 | |
| 11 | 2022 | 4 | |
| 12 | 2022 | 3 | |
| 13 | 2023 | 2 | |
| 14 | 2023 | 0 | |
| 15 | 2025 | 0 | |
| 16 | 2024 | 0 | |
| 17 | An Efficient Approach for Edge Detection Hardware Accelerator for Real Time Video Segmentation using Laplacian Operator | 2014 | 0 |
About S. Premkumar
S. Premkumar is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence, having authored 17 papers that have together received 192 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (4 papers), Blockchain Technology Applications and Security (3 papers), Cloud Computing and Resource Management (3 papers), Smart Agriculture and AI (3 papers), Brain Tumor Detection and Classification (2 papers), IoT Networks and Protocols (2 papers), AI in cancer detection (1 paper) and Advanced Technology in Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (59 citations), Health Information Management (10 citations), Computer Vision and Pattern Recognition (41 citations), Computer Networks and Communications (34 citations) and Neurology (11 citations). S. Premkumar has collaborated with scholars based in India. Frequent co-authors include S. Velliangiri, Vani Rajasekar, Arun Narayanan, Dankan Gowda, M. A. Gopinath, Naziya Hussain, KDV Prasad, Lalitha Subramanian, R. Seetharaman and S. Sivakumar. Their work appears in journals such as Knowledge-Based Systems, Results in Engineering, Network Computation in Neural Systems, Journal of Water Process Engineering and Computational 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.