arxiv:2404.01049

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

Published on Apr 1, 2024

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Abstract

The paper uses a sector-based CNN methodology with SDSS-DR18 data to achieve high performance in star-galaxy classification, offering a promising approach for real-time astronomical analysis.

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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.

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