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Arxiv
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EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network
- Electroencephalogram (EEG) is a valuable technique for analyzing brain activity.
- Existing Graph Signal Processing (GSP) studies lack interpretability and prediction confidence.
- EEG-GMACN is introduced to enhance interpretability and credibility of EEG classification.
- The study improves transparency and effectiveness of EEG analysis for clinical and neuroscience research.
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