amrzhd/EEG-MSCNN

This project explores the impact of Multi-Scale CNNs on the classification of EEG signals in Brain-Computer Interface (BCI) systems. By comparing the performance of two models, EEGNet and MSTANN, the study demonstrates how richer temporal feature extractions can enhance CNN models in classifying EEG signals

语言：Jupyter Notebook · GitHub 星标：79 · Fork：1

话题：bci · bci-systems · deep-learning · eeg-signals · eegnet · machine-learning · multi-scale-features · signal-processing

在 GitHub 上查看原仓库