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galmask: A Python package for unsupervised galaxy masking

Instrumentation and Methods for Astrophysics 2022-06-15 v1

Abstract

Galaxy morphological classification is a fundamental aspect of galaxy formation and evolution studies. Various machine learning tools have been developed for automated pipeline analysis of large-scale surveys, enabling a fast search for objects of interest. However, crowded regions in the image may pose a challenge as they can lead to bias in the learning algorithm. In this Research Note, we present galmask, an open-source package for unsupervised galaxy masking to isolate the central object of interest in the image. galmask is written in Python and can be installed from PyPI via the pip command.

Keywords

Cite

@article{arxiv.2206.06787,
  title  = {galmask: A Python package for unsupervised galaxy masking},
  author = {Yash Gondhalekar and Rafael S. de Souza and Ana L. Chies-Santos},
  journal= {arXiv preprint arXiv:2206.06787},
  year   = {2022}
}

Comments

Submitted to RNAAS

R2 v1 2026-06-24T11:50:39.169Z