galaxyclassifier

The "Machine learning for morphological galaxy classification" is a repository for classifying Galaxy Zoo 2 (GZ2) images into (1) Galaxy and Non-Galaxy, and (2) Galaxy in Spiral, Elliptical, and Odd objects using the five state-of-the-art machine learning models.

Overview

We employed five different classification models, including:

1. Support Vector Machine (SVM) with Zernike moments (ZMs)
2. 1D-Convolutional Neural Network (1D-CNN) with ZMs
3. 2D-CNN with Vision Transformer (ViT) and original images
4. ResNet50 with ViT and original images
5. VGG16 with ViT and original images

The SVM and 1D-CNN models utilized Zernike moments (ZMs) extracted from the images, while the 2D-CNN, ResNet5, and VGG16 with Vision Transformer (ViT) models were designed based on the original images.

You can see the full notebooks and data in:
https://github.com/hmddev1/machine_learning_for_morphological_galaxy_classification/tree/main

and the full changelog in:
https://github.com/hmddev1/machine_learning_for_morphological_galaxy_classification/commits/v0.1