A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification
Instrumentation and Methods for Astrophysics
2024-06-21 v1 Machine Learning
Abstract
This paper introduces a novel sector-based methodology for star-galaxy classification, leveraging the latest Sloan Digital Sky Survey data (SDSS-DR18). By strategically segmenting the sky into sectors aligned with SDSS observational patterns and employing a dedicated convolutional neural network (CNN), we achieve state-of-the-art performance for star galaxy classification. Our preliminary results demonstrate a promising pathway for efficient and precise astronomical analysis, especially in real-time observational settings.
Cite
@article{arxiv.2404.01049,
title = {A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification},
author = {Anumanchi Agastya Sai Ram Likhit and Divyansh Tripathi and Akshay Agarwal},
journal= {arXiv preprint arXiv:2404.01049},
year = {2024}
}