Galaxy Morphological Classification with Zernike Moments and Machine Learning Approaches

Galaxy Morphological Classification with Zernike Moments and Machine Learning Approaches

Classifying galaxies is an essential step for studying their structures and dynamics. Using GalaxyZoo2 (GZ2) fractions thresholds, we collect 545 and 11,735 samples in nongalaxy and galaxy classes, respectively. We compute the Zernike moments (ZMs) for GZ2 images, extracting unique and independent c...

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Bibliographic Details
Main Authors: Hamed Ghaderi, Nasibe Alipour, Hossein Safari
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal Supplement Series
Subjects:
Galaxy classification systems
Galaxy structure
Spiral galaxies
Elliptical galaxies
Online Access:https://doi.org/10.3847/1538-4365/ada8ab
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