A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification
<|reference_start|>A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification: 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.<|reference_end|>
@article{likhit2024a,
    title={A Novel Sector-Based Algorithm for an Optimized Star-Galaxy
  Classification},
    author={Anumanchi Agastya Sai Ram Likhit, Divyansh Tripathi, Akshay Agarwal},
    journal={The Second Tiny Papers Track at ICLR 2024},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.01049},
    primaryClass={astro-ph.IM cs.LG}
}