Beyond the Hubble Sequence — Exploring Galaxy Morphology with Unsupervised Machine Learning
Conventionally, galaxy morphological classifications are defined by visual assessment. However, visual classification systems such as Hubble types can be intrinsically biased due to the subjective judgement of human classifiers. Additionally, since morphological "classifications" into types is an important and complementary process, it is not clear
Cheng, T. et al.
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2021