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.

Detalhes bibliográficos
Principais autores: Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Outros Autores: Nahim, Nabuat Zaman
Formato: Tese
Idioma:English
Publicado em: Brac University 2024
Assuntos:
fMRI data
Deep learning
Sleep stage detection
ConvLSTM model
LSTM
EEG data
Signal processing > Digital techniques.
Machine learning.
Electroencephalography.
Acesso em linha:http://hdl.handle.net/10361/24267

Internet

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

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