论文标题
加尔马斯克：用于无监督的星系掩模的Python包装
galmask: A Python package for unsupervised galaxy masking
论文作者
论文摘要
星系形态分类是星系形成和进化研究的基本方面。已经开发了各种机器学习工具，用于对大规模调查的自动管道分析，从而快速搜索感兴趣的对象。但是，图像中拥挤的地区可能会构成挑战，因为它们可能导致学习算法的偏见。在本研究说明中，我们提出了Galmask，这是一种开源包，用于无监督的Galaxy屏蔽，以隔离图像中感兴趣的中心对象。 Galmask用Python编写，可以通过PIP命令从PYPI安装。
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.
