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.

Podrobná bibliografie
Hlavní autoři: Tanvir, Farhan, Rahman, Tanjilur, Kamal, S M Arfa, Hassan, Mahmudul, Nazia, Nowshin
Další autoři: Nahim, Nabuat Zaman
Médium: Diplomová práce
Jazyk:English
Vydáno: Brac University 2024
Témata:
fMRI data
Deep learning
Sleep stage detection
ConvLSTM model
LSTM
EEG data
Signal processing > Digital techniques.
Machine learning.
Electroencephalography.
On-line přístup:http://hdl.handle.net/10361/24267

Internet

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

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