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…