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Power efficient machine learning-based hardware architectures for biomedical applications
(University of Missouri--Columbia, 2023)
The future of critical health diagnosis will involve intelligent and smart devices that are low-cost, wearable, and lightweight, requiring low-power, energy-efficient hardware platforms. Various machine learning models, ...