NYCU Deep Learning and Practice Summer 2023

EEGnet on a microcontroller

Final project for the course Human Data Analytics (UniPD)

Machine Learning based Brain Computer Interface (BCI) by analyzing EEG Data using PyTorch

NCTU(NYCU) Deep Learning and Practice Spring 2021

NYU CS-GY 9223 E Neuroinformatics (Spring 2024) - Final Project

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.

Clasificador de cognitive tasks para señales EEG basado en EEGNet utilizando el dataset de Aunon y Keirn (1989)

Stage training Implementation

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

Processing EEG data using Speechbrain-MOABB and model tuning to get best results

PyTorch code for "Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training"

Labs for 5003 Deep Learning Practice course in summer term 2021 at NYCU.

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".

Project for XAI606(Korea University)

EEG Classification API using Flask

This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.

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

The codes that I implemented during my B.Sc. project.

Class to automatic create Convolutional Neural Network in PyTorch