Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification

Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Библиографические подробности
Главные авторы:	Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Другие авторы:	Nahim, Nabuat Zaman
Формат:	Диссертация
Язык:	English
Опубликовано:	Brac University 2024
Предметы:	fMRI data Deep learning Sleep stage detection ConvLSTM model LSTM EEG data Signal processing > Digital techniques. Machine learning. Electroencephalography.
Online-ссылка:	http://hdl.handle.net/10361/24267

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