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.

Bibliographic Details
Main Authors: Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Other Authors: Nahim, Nabuat Zaman
Format: Thesis
Language:English
Published: Brac University 2024
Subjects:
fMRI data
Deep learning
Sleep stage detection
ConvLSTM model
LSTM
EEG data
Signal processing > Digital techniques.
Machine learning.
Electroencephalography.
Online Access:http://hdl.handle.net/10361/24267

Internet

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

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