Trending repositories for topic brain-computer-interface
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers
A wheelchair controlled by EEG brain signals and enhanced with assisted driving
Low Cost Electroencephalogram Based Brain-Computer-Interface
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
A wheelchair controlled by EEG brain signals and enhanced with assisted driving
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Low Cost Electroencephalogram Based Brain-Computer-Interface
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
Implementation of "From Word Embedding to Reading Embedding Using Large Language Model, EEG and Eye-tracking"
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification
Low Cost Electroencephalogram Based Brain-Computer-Interface
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
A MATLAB package for modelling multivariate stimulus-response data
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)
Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers
Documentation for Reproducing & Using the OpenBCI cEEGrid Adapter
Implementation of ConvLSTM in pytorch applied for BCI (Brain Machine Interface) following paper: Convolutional LSTM Network-A Machine Learning Approach for Precipitation Nowcasting
Implementation of "From Word Embedding to Reading Embedding Using Large Language Model, EEG and Eye-tracking"
List of summer schools to study brain-computer interfaces, neurotechnology & related fields worldwide
Feature extraction and prediction of human neural signals, using chaos theory, dynamical systems theory, various physics/maths theories, RNN, CNN, transformers
Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification
code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"
Documentation for Reproducing & Using the OpenBCI cEEGrid Adapter
PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware
Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
Must-read papers on machine learning, deep learning, reinforcement learning and other learning methods for brain-computer interfaces.
A MATLAB package for modelling multivariate stimulus-response data
End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification (IEEE Transactions on Biomedical Engineering)
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
Low Cost Electroencephalogram Based Brain-Computer-Interface
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python