ADHDeepNet is a model that integrates temporal and spatial characterization, attention modules, and explainability techniques, optimized for EEG data ADAD diagnosis. Neural Architecture Search (NAS), Hyper-parameter optimization, and data augmentation are also incorporated to enhance the model's performance and accuracy.
deep-learning cnn eeg-signals inception t-sne adhd interpretability eegnet squeeze-and-excitation-networks weight-visualization
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Updated
Jun 25, 2024 - Jupyter Notebook