Deep Learning pipeline for motor-imagery classification.
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Updated
Jan 9, 2022 - Python
Deep Learning pipeline for motor-imagery classification.
The codes that I implemented during my B.Sc. project.
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
PyTorch code for "Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training"
Class to automatic create Convolutional Neural Network in PyTorch
Labs for 5003 Deep Learning Practice course in summer term 2021 at NYCU.
NCTU(NYCU) Deep Learning and Practice Spring 2021
EEG Classification API using Flask
Machine Learning based Brain Computer Interface (BCI) by analyzing EEG Data using PyTorch
Stage training Implementation
Project for XAI606(Korea University)
NYCU Deep Learning and Practice Summer 2023
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