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.

Detalles Bibliográficos
Autores principales: Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Otros Autores: Nahim, Nabuat Zaman
Formato: Tesis
Lenguaje:English
Publicado: Brac University 2024
Materias:
fMRI data
Deep learning
Sleep stage detection
ConvLSTM model
LSTM
EEG data
Signal processing > Digital techniques.
Machine learning.
Electroencephalography.
Acceso en línea:http://hdl.handle.net/10361/24267

Internet

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

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