galaxy-classification

A python-based tool to fetch astronomical images 🌌

Repo for my thesis research development at UC Riverside: "Classifying Galaxy Morphologies Using Bayesian Neural Networks for LSST"

SDSS telescopes have captured over 40 TB worth of galaxy images and classification of these images is the first step towards obtaining a deeper understanding of physical processes within them, star formation, and the nature of the universe. Since we could not find an easily accessible dataset for galaxy classification, we compiled a dataset for …

My thesis on five best ML/DL models for galaxies and non-galaxy classification obtain new method for feature extraction.

autonomous astronomical anomaly discovery system

This repository contains the code and data for the Astronomical Object Classification Project. The project focuses on classifying celestial objects (stars, galaxies, and quasars) based on their spectral characteristics using data from the Sloan Digital Sky Survey (SDSS).

A Bayesian CNN approach to SDSS image data classification

Galaxy Classification using CNN

Binary classification of spiral galaxies (barred vs unbarred) from GALEX NUV FITS images using morphological feature extraction and classical ML classifiers.

Experiments in galaxy classification using CNNs on data frovided by Kaggle

Deep-learning galaxy morphology classifier — EfficientNet-B0 fine-tuned on Galaxy Zoo 2, served via FastAPI with a Next.js + Three.js front-end that classifies a live gallery and any image you upload.

Reproducible end-to-end ML pipeline for galaxy morphology classification - companion code to a review article on ML in modern astronomy

Deep learning project for galaxy image classification using a custom CNN and transfer learning with DenseNet121.

Computer vision project using CNNs to classify galaxies based on morphological features from the Galaxy Zoo 2 dataset.

A morphological galaxy classification program using machine learning.

Explainable AI for galaxy morphology classification using deep learning techniques.

Deep learning pipeline for automated galaxy morphology classification (GalZoo-style) using CNNs + Grad-CAM interpretability.

Galaxy morphology classification and photometric redshift estimation using Galaxy Zoo and SDSS

Visual Galaxy Classification Using Convolutional Neural Networks

Neural-network classification of SDSS galaxies, quasars and stars using PyTorch.