Deep-Transfer-Learning-with-CNN-for-EEG-signals-in-diagnosing-Schizophrenia-patients.

We propose an automated method that utilizes transfer learning with deep convolutional neural networks (CNNs) to differentiate individuals with SZ from healthy controls. Initially, we transform EEG signals into images using a time-frequency technique known as the continuous wavelet transform (CWT). Subsequently, these EEG signal images are inputted into our CNN model.