Convolutional Neural Networks in the Detection of Astronomical Objects from the Messier Catalog

  • Witold Beluch Faculty of Mechanical Engineering, Silesian University of Technology, Gliwice, Poland
  • Paweł Śliwa Faculty of Mechanical Engineering, Silesian University of Technology, Gliwice, Poland

Abstract

This paper explores the application of convolutional neural networks in the field of amateur astronomy. The authors have employed the available astronomical datasets to develop a detector for identifying astronomical objects from the Messier catalog. A concept framework for creating such a detector for astronomical objects using artificial intelligence tools in the form of a detector based on convolutional neural networks is presented. Augmentation and pre-processing procedures have been used to extend the feature distribution in the training set. Examples confirming the effectiveness of the proposed detector of astronomical objects are presented.

Keywords

convolutional neural networks, astronomical objects detection, Messier catalog,

References

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Published
Oct 2, 2023
How to Cite
BELUCH, Witold; ŚLIWA, Paweł. Convolutional Neural Networks in the Detection of Astronomical Objects from the Messier Catalog. Computer Assisted Methods in Engineering and Science, [S.l.], v. 30, n. 4, p. 461–479, oct. 2023. ISSN 2956-5839. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/527>. Date accessed: 21 june 2024. doi: http://dx.doi.org/10.24423/cames.527.
Section
Articles