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Vetriveeran Rajamani on Muck Rack

Vetriveeran Rajamani

As seen in: Frontiers in Digital Health, MDPI
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Articles

Hardware-aware knowledge-distilled CNN for real-time classification of plaque-associated angiographic findings on FPGA

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By Vetriveeran Rajamani, Nazarkar Pravalika, Jabeena Afthab
| Frontiers in Digital Health
Abstract Coronary artery disease (CAD) is one of the leading causes of global mortality, necessitating accurate assessment of coronary artery stenosis and plaque-associated angiographic findings from coronary angiography images. Although deep learning-based diagnostic models have demonstrated high predictive capability, their deployment on resource-constrained embedded platforms remains challenging because of computational complexity and memory requirements.
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Modeling Excitable Cells with Memristors

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By Maheshwar Sah, Alon Ascoli, Ronald Tetzlaff, Vetriveeran Rajamani
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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