eegnet
There are 24 repositories under eegnet topic.
aliasvishnu/EEGNet
[Old version] PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces - https://arxiv.org/pdf/1611.08024.pdf
amrzhd/EEGNet
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
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
High-East/BCI-ToolBox
Deep Learning pipeline for motor-imagery classification.
arkanivasarkar/EEG-Data-Augmentation-using-Variational-Autoencoder
Improving performance of motor imagery classification using variational-autoencoder and synthetic EEG signals
AliAmini93/ADHDeepNet
ADHDeepNet is a model that integrates temporal and spatial characterization, attention modules, and explainability techniques, optimized for EEG data ADAD diagnosis. Neural Architecture Search (NAS), Hyper-parameter optimization, and data augmentation are also incorporated to enhance the model's performance and accuracy.
IoBT-VISTEC/EEGANet
EEG Artifact Removal Using Deep Learning (source code, IEEE Journal of Biomedical and Health Informatics)
Amir-Hofo/EEGNet_Pytorch
This code implements the EEG Net deep learning model using PyTorch. The EEG Net model is based on the research paper titled "EEGNet: A Compact Convolutional Neural Network for EEG-based Brain-Computer Interfaces".
Pooria90/EEG-Motor-Imagery-Analysis
The codes that I implemented during my B.Sc. project.
gzoumpourlis/Ensemble-MI
PyTorch code for "Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training"
secondlevel/EEG-classification
It is the task to classify BCI competition datasets (EEG signals) using EEGNet and DeepConvNet with different activation functions. You can get some detailed introduction and experimental results in the link below. https://github.com/secondlevel/EEG-classification/blob/main/Experiment%20Report.pdf
jesus-333/Dynamic-PyTorch-Net
Class to automatic create Convolutional Neural Network in PyTorch
eneriz-daniel/MIBCI-QCNNs
This repo contains the source code of the project "FPGA implementation of BCIs using QCNNs" submitted to the Xilinx Open Hardware Design Competition 2021.
joycenerd/Deep_Learning_Practice_labs
Labs for 5003 Deep Learning Practice course in summer term 2021 at NYCU.
steven112163/Deep-Learning-and-Practice
NCTU(NYCU) Deep Learning and Practice Spring 2021
phanquanghung/eeg-classification-api
EEG Classification API using Flask
aspyridakos/EEG-Based-Motor-Imagery-Decoding-with-Deep-Learning
Processing EEG data using Speechbrain-MOABB and model tuning to get best results
mj-sam/stage-trans
Stage training Implementation
PhilKes/ML-BCI
Machine Learning based Brain Computer Interface (BCI) by analyzing EEG Data using PyTorch
High-East/XAI606-EEGNet
Project for XAI606(Korea University)
MarceloContreras/Proyecto-EEGNet-
Clasificador de cognitive tasks para señales EEG basado en EEGNet utilizando el dataset de Aunon y Keirn (1989)
NhanUTS/EEGnet_MCU
EEGnet on a microcontroller
aisu-programming/Preprocessor-for-EEG-Signals
NYU CS-GY 9223 E Neuroinformatics (Spring 2024) - Final Project
ra890927/NYCU_Deep_Learning
NYCU Deep Learning and Practice Summer 2023