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

Anumanchi Agastya Sai Ram Likhit, Divyansh Tripathi, Akshay Agarwal
4/1/2024
astro-ph.IMcs.LG

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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.

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Cite this paper

@article{likhit2024novel,
  title  = {A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification},
  author = {Anumanchi Agastya Sai Ram Likhit and Divyansh Tripathi and Akshay Agarwal},
  year   = {2024},
  eprint = {2404.01049},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.01049v1}
}

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