Hao-Yun Chang's repositories
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
NYCU-110-2-Natural-Language-Processing
It is the nlp task to classify empathetic dialogues datasets using RoBERTa, ERNIE-2.0 and XLNet with different preprocessing method. You can get some detailed introduction and experimental results in the link below.
Diabetic-Retinopathy-Detection
It is the image classification task to classify Diabetic-Retinopathy category using ResNet18, ResNet50 pretrained model. which is related to kaggle competition. The kaggle competition link can found below. https://www.kaggle.com/c/diabetic-retinopathy-detection#description
Cifar10-Classification
Pattern Recognition homework5 in NYCU It is the task to classify CIFAR10 datasets using Vision Transformer. You can get some detailed introduction and experimental results in the link below. https://github.com/secondlevel/Cifar10-Classification/blob/main/310551031_HW5.pdf
Back-propagation
It's only using Numpy packages to build two-layer neural network. You can get some detailed introduction and experimental results in the link below. https://github.com/secondlevel/Back-propagation/blob/main/Experiment%20Report.pdf
Deep-Q-Network-and-Deep-Deterministic-Policy-Gradient
This project uses the pytorch package to implement DQN and DDPG models to automate the LunarLander-v2 and LunarLanderContinuous-v2 games.
nsdhw_21au
This is the homework about Numerical Software Development (NYCU 2021 autumn).
NYCU-UNIX-Programming
This is the summarize of unix program homework.
Social-distance-detector
The purpose of this project aims to calibrate the camera with a frame sequence containing a chessboard, so the input will be the image and the output will be the camera matrix.
Conditional-Sequence-to-Sequence-VAE
This is the Lab4 of the Summer course
Fisher-linear-discriminant
Pattern Recognition homework2 in NYCU. This project is to implement Fisher’s linear discriminant by using only NumPy.
Decision-Tree
Pattern Recognition homework3 in NYCU. This project is to implement the Decision Tree, AdaBoost and Random Forest algorithm by using only NumPy.
Linear-Regression
Pattern Recognition homework1 in NYCU. This project is to implement linear regression by using only NumPy with Gradient Descent.
Support-Vector-Machine
Pattern Recognition homework4 in NYCU. This project is to implement the cross-validation and grid search using only NumPy and train the SVM model.