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.

Bibliografiska uppgifter
Huvudupphovsmän: Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Övriga upphovsmän: Nahim, Nabuat Zaman
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2024
Ämnen:
fMRI data
Deep learning
Sleep stage detection
ConvLSTM model
LSTM
EEG data
Signal processing > Digital techniques.
Machine learning.
Electroencephalography.
Länkar:http://hdl.handle.net/10361/24267

Internet

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

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