S. Sekar
Impact in
- Numerical Analysis top 10%
- Numerical methods for differential equations
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- Brain Tumor Detection and Classification
Papers in
-
- Numerical methods for differential equations 13
- Differential Equations and Numerical Methods 9
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- Fractional Differential Equations Solutions 16
- Co-authors
- T. Rajendran (5 shared papers)G. Charlyn Pushpa Latha (4 shared papers)V. Selladurai (1 shared paper)K. Murugesan (7 shared papers)K. Maheswari (1 shared paper)S. Ramkumar (2 shared papers)T. Anitha (5 shared papers)D. J. Evans (4 shared papers)
- Journals
- Polymers for Advanced Technologies (2 papers)Network Computation in Neural Systems (1 paper)Journal of Ambient Intelligence and Humanized Computing (1 paper)Psychopharmacology (1 paper)European Neuropsychopharmacology (1 paper)
- Partner nations
- IndiaSouth KoreaUnited Kingdom
In The Last Decade
S. Sekar
46 papers receiving 313 citations
Peers
Comparison fields: 5 of 104
- Numerical Analysis 39
- Neurology 54
- Modeling and Simulation 28
- Health Informatics 6
- Computer Vision and Pattern Recognition 72
Countries citing papers authored by S. Sekar
This map shows the geographic impact of S. Sekar'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. Sekar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Sekar more than expected).
Fields of papers citing papers by S. Sekar
This network shows the impact of papers produced by S. Sekar. 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. Sekar. The network helps show where S. Sekar may publish in the future.
Co-authors
The 25 scholars most cited alongside S. Sekar, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 60 | |
| 2 | 2009 | 42 | |
| 3 | 2020 | 31 | |
| 4 | 2022 | 21 | |
| 5 | 2013 | 18 | |
| 6 | 2022 | 17 | |
| 7 | 2010 | 16 | |
| 8 | 2022 | 15 | |
| 9 | 2004 | 14 | |
| 10 | 2023 | 13 | |
| 11 | 2004 | 13 | |
| 12 | 2004 | 8 | |
| 13 | 2021 | 7 | |
| 14 | 2023 | 5 | |
| 15 | 2004 | 5 | |
| 16 | 2024 | 4 | |
| 17 | Cardio-Vascular Disease Classification Using Stacked Segmentation Model and Convolutional Neural Networks | 2020 | 4 |
| 18 | 2013 | 4 | |
| 19 | 2017 | 3 | |
| 20 | 2006 | 3 |
About S. Sekar
S. Sekar is a scholar working on Numerical Analysis, Modeling and Simulation, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Applied Mathematics, having authored 56 papers that have together received 344 indexed citations. Recurring topics across this work include Fractional Differential Equations Solutions (16 papers), Numerical methods for differential equations (13 papers), Differential Equations and Numerical Methods (9 papers), Matrix Theory and Algorithms (8 papers), Nonlinear Differential Equations Analysis (6 papers), Fuzzy Systems and Optimization (6 papers), COVID-19 diagnosis using AI (3 papers) and Electromagnetic Simulation and Numerical Methods (3 papers). The work is most often cited by research in Numerical Analysis (39 citations), Neurology (54 citations), Modeling and Simulation (28 citations), Health Informatics (6 citations) and Computer Vision and Pattern Recognition (72 citations). S. Sekar has collaborated with scholars based in India, South Korea and United Kingdom. Frequent co-authors include T. Rajendran, G. Charlyn Pushpa Latha, V. Selladurai, K. Murugesan, K. Maheswari, S. Ramkumar, T. Anitha, D. J. Evans, P. Sriramakrishnan and A. Priya. Their work appears in journals such as Polymers for Advanced Technologies, Network Computation in Neural Systems, Journal of Ambient Intelligence and Humanized Computing, Psychopharmacology and European Neuropsychopharmacology.
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.