Deep learning based arrhythmia classification on low-cost and low-compute MCU

Deep learning based arrhythmia classification on low-cost and low-compute MCU

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Détails bibliographiques
Auteurs principaux:	Zishan, Md Abu Obaida, Shihab, H M, Rahman, Gazi Mashrur, Islam, Sabik Sadman, Riya, Maliha Alam
Autres auteurs:	Mukta, Jannatun Noor
Format:	Thèse
Langue:	English
Publié:	Brac University 2023
Sujets:	ECG Arrhythmia Low-cost Low-compute Low-power Machine learning Micro-controller Cognitive learning theory (Deep learning)
Accès en ligne:	http://hdl.handle.net/10361/22018

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