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.

Dettagli Bibliografici
Autori principali:	Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Altri autori:	Nahim, Nabuat Zaman
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2024
Soggetti:	fMRI data Deep learning Sleep stage detection ConvLSTM model LSTM EEG data Signal processing > Digital techniques. Machine learning. Electroencephalography.
Accesso online:	http://hdl.handle.net/10361/24267

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