Analysis of Deep Learning Models for EEG Data Processing

This content delves into the application of deep learning models, such as Sequential Modeler, Feature Extraction, and Discriminator, for processing EEG data from the TUH EEG Corpus. The architecture involves various layers like Convolution, Max Pooling, ReLU activation, and Dropout. It explores temp

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