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.

Opis bibliograficzny
Główni autorzy:	Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Kolejni autorzy:	Nahim, Nabuat Zaman
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2024
Hasła przedmiotowe:	fMRI data Deep learning Sleep stage detection ConvLSTM model LSTM EEG data Signal processing > Digital techniques. Machine learning. Electroencephalography.
Dostęp online:	http://hdl.handle.net/10361/24267

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