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.

Dettagli Bibliografici
Autori principali:	Zishan, Md Abu Obaida, Shihab, H M, Rahman, Gazi Mashrur, Islam, Sabik Sadman, Riya, Maliha Alam
Altri autori:	Mukta, Jannatun Noor
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2023
Soggetti:	ECG Arrhythmia Low-cost Low-compute Low-power Machine learning Micro-controller Cognitive learning theory (Deep learning)
Accesso online:	http://hdl.handle.net/10361/22018

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