3 papers
astro-ph.GA2024
An efficient unsupervised classification model for galaxy morphology: Voting clustering based on coding from ConvNeXt large model
Guanwen Fang, Yao Dai, Zesen Lin +6
In this work, we update the unsupervised machine learning (UML) step by proposing an algorithm based on ConvNeXt large model coding to improve the efficiency of unlabeled galaxy mo…
astro-ph.GA2024
Preparation for CSST: Star-galaxy Classification using a Rotationally Invariant Supervised Machine Learning Method
Shiliang Zhang, Guanwen Fang, Jie Song +6
Most existing star-galaxy classifiers depend on the reduced information from catalogs, necessitating careful data processing and feature extraction. In this study, we employ a supe…
astro-ph.GA2024
USmorph: An Updated Framework of Automatic Classification of Galaxy Morphologies and Its Application to Galaxies in the COSMOS Field
Jie Song, GuanWen Fang, Shuo Ba +9
Morphological classification conveys abundant information on the formation, evolution, and environment of galaxies. In this work, we refine the two-step galaxy morphological classi…