Statistics for topic eeg
RepositoryStats tracks 567,266 Github repositories, of these 122 are tagged with the eeg topic. The most common primary language for repositories using this topic is Python (67). Other languages include: Jupyter Notebook (16), MATLAB (14)
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A curated list of awesome neuroscience libraries, software and any content related to the domain.
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College L...
Code for the paper "Multi-Task CNN Model for Emotion Recognition from EEG Brain Maps". DEAP dataset. Python/Keras/Tensorflow 2 Impementation.
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
An R package for processing and plotting of electroencephalography (EEG) data
Code for the paper "Multi-Task CNN Model for Emotion Recognition from EEG Brain Maps". DEAP dataset. Python/Keras/Tensorflow 2 Impementation.
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College L...
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
An R package for processing and plotting of electroencephalography (EEG) data
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
A curated list of awesome neuroscience libraries, software and any content related to the domain.
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
PyPREP: A Python implementation of the Preprocessing Pipeline (PREP) for EEG data
Attention temporal convolutional network for EEG-based motor imagery classification
Code for the paper "Multi-Task CNN Model for Emotion Recognition from EEG Brain Maps". DEAP dataset. Python/Keras/Tensorflow 2 Impementation.
NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG
selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data
PyPREP: A Python implementation of the Preprocessing Pipeline (PREP) for EEG data
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) 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
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG
selfEEG: a Python library for Self-Supervised Learning on Electroencephalography (EEG) data
A Convolutional Transformer to decode mental states from Electroencephalography (EEG) for Brain-Computer Interfaces (BCI)
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
Code for the paper published in Deep Generative Models for Health Workshop at the Neurips 2023.
A Convolutional Transformer to decode mental states from Electroencephalography (EEG) for Brain-Computer Interfaces (BCI)
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) 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
EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
Local-first behavior tracking and brain recording app. Discord: https://discord.gg/sqsuzXWE3K
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 mode...
[IEEE JBHI] "MultiChannelSleepNet: A Transformer-Based Model for Automatic Sleep Stage Classification With PSG"
Attention temporal convolutional network for EEG-based motor imagery classification