HIGHLIGHTS
SUMMARY
Deep learning has gained immense popularity due to its ability to automate feature selection and extraction processes (Chiarelli et_al, 2018; Trakoolwilaiwan et_al, 2018; Tanveer et_al, 2019; Janani et_al, 2020). Convolutional Neural_Networks (CNN) are trained commonly for image classification (O`Shea and Nash, 2015; Nguyen et_al, 2019; Olmos et_al, 2019) and consist of convolutional layers for feature extraction from images. The choice of the brain signals acquired and the features selected for feedback form essential steps in BCI development (Benitez-Andonegui et_al, 2020; Rieke et_al, 2020). This neuroimaging modality has recently been utilized to analyze . . .
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