A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
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Updated
Jan 19, 2023 - Python
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Motor Imagery EEG signal Classification on DWT
Improving performance of motor imagery classification using variational-autoencoder and synthetic EEG signals
Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence
Deep Learning pipeline for motor-imagery classification.
Project to test the accuracy of multiple algorithms published in articles to the EEG binary motor imagery problem
EEG Motor Imagery Classification Using CNN, Transformer, and MLP
Rethinking CNN Architecture for Enhancing Decoding Performance of Motor Imagery-based EEG Signals
Using Deep Learning techniques to classify Motor Imagery Electroencephalography (EEG) signals
A research repository of deep learning on electroencephalographic (EEG) for Motor imagery(MI), including eeg data processing(visualization & analysis), papers(research and summary), deep learning models(reproduction and experiments).
This repository contains all the code used in the experiments of the paper Restricted Exhaustive Search for Frequency Band Selection in Motor Imagery Classification as well as additional information of the experiments and results, and how to reproduce them.
Towards Domain Free Transformer for Generalized EEG Pre-training
Implementation of Convolutional Recurrent Neural Network (CRNN) to decode motor imagery EEG data.
Record EEG data from a Muse 2 headband using the MInd Monitor app and python osc module. Build and train a CNN model in Keras framework to classify Left-Right Motor Imagery. Make real-time predictions using the trained model.
Maxim Entropy based Common Spatial Pattern
Motor Imagery System Using a Low-Cost EEG Brain Computer Interface.
This code is for classifying spectrogram images of Motor Movement/Imagery tasks using a Convolutional Neural Network (CNN) and Generative Adversarial Network (GAN) for data augmentation..
A MATLAB toolbox for classification of motor imagery tasks in EEG-based BCI system with CSP, FB-CSP and BSSFO
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