Paper ID: 2404.01049

A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification

Anumanchi Agastya Sai Ram Likhit, Divyansh Tripathi, Akshay Agarwal

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.

Submitted: Apr 1, 2024