Application of deep neural networks in electroencephalography (EEG)
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Abstract (EN)
This study aims to evaluate the effectiveness of deep learning techniques in the classification of EEG signals by investigating the application of deep neural networks (DNN) in electroencephalography (EEG). Convolutional neural network (CNN) models developed using the BCI Competition III dataset were tested in motor imagery (MI) classification and showed superior performance compared to traditional methods. The research aims to contribute to the development of EEG-based Brain-Computer Interface (BCI) systems.
Author
Beray İkinci
Institution
İstanbul Gelişim University
Elektrik Elektronik Mühendisliği Bilim Dalı
How to Cite
Beray İkinci (Master Thesis). Application of deep neural networks in electroencephalography (EEG), 2025, İstanbul Gelişim University.
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