Connolly et al. (2021): „Machine learning in galaxy morphology, Annual Review of Astronomy and Astrophysics

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Machine Learning in Galaxy Morphology: Insights from Connolly et al. (2021)
An SEO-Optimized Review Article for Annual Review of Astronomy and Astrophysics --- Unlocking the Cosmos: How Machine Learning Transforms Galaxy Morphology—Insights from Connolly et al. (2021) In the ever-evolving quest to understand the universe, galaxy morphology stands as a cornerstone of observational astrophysics. The shapes, structures, and classifications of galaxies hold vital clues about their formation, evolution, and the underlying physics of cosmic growth. Yet, analyzing millions of galaxies to discern subtle morphological patterns has long challenged even the largest research teams. Enter machine learning—a revolutionary tool reshaping how astronomers classify and interpret galactic forms.