An Attention-Based Architecture for EEG Classification

The objective of An Attention-Based Architecture for EEG Classification is to develop a machine learning model that can accurately classify electroencephalogram (EEG) signals using an attention-based architecture. The model uses various data analysis and machine learning techniques to identify patterns and classify EEG signals.