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.

Détails bibliographiques
Auteurs principaux: Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Autres auteurs: Nahim, Nabuat Zaman
Format: Thèse
Langue:English
Publié: Brac University 2024
Sujets:
fMRI data
Deep learning
Sleep stage detection
ConvLSTM model
LSTM
EEG data
Signal processing > Digital techniques.
Machine learning.
Electroencephalography.
Accès en ligne:http://hdl.handle.net/10361/24267

Internet

http://hdl.handle.net/10361/24267

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