#计算机科学#An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
翻译 - 一个开放的软件包，用于开发基于 BCI 的大脑和认知计算技术，用于使用深度学习识别用户的意图
Attention temporal convolutional network for EEG-based motor imagery classification
EEG Motor Imagery Tasks Classification (by Channels) via Convolutional Neural Networks (CNNs) based on TensorFlow
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
#计算机科学#Source Code for "Adaptive Transfer Learning with Deep CNN for EEG Motor Imagery Classification".
Matlab source code of the paper "D. Wu, X. Jiang, R. Peng, W. Kong, J. Huang and Z. Zeng, Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline, Information Sciences...
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...
Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces (MEKT)
Motor Imagery EEG Signal Classification Using Random Subspace Ensemble Network
The decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for standing and sitting. (IEEE Sensors Journal)
Implementation of filter bank common spatial pattern (FBCSP) for MI-based BCI in python
Official code for "Attention-Based Spatio-Temporal-Spectral Feature Learning for Subject-Specific EEG Classification" paper
#计算机科学#Towards Domain Free Transformer for Generalized EEG Pre-training
EEG BCI Real-Time Applications: Contains real-time demonstrations of BCI applications
#计算机科学#A trusted repository for groundbreaking EEG research code. Some peer-reviewed algorithms (such as EEG data augmentation techniques, EEG classification models) to push the boundaries of neuroscience.
#计算机科学#The codes that I implemented during my B.Sc. project.
In AugmentBrain we investigate the performance of different data augmentation methods for the classification of Motor Imagery (MI) data using a Convolutional Neural Network tailored for EEG named EEGN...
Project to test the accuracy of multiple algorithms published in articles to the EEG binary motor imagery problem