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Found 3 papers, 1 papers with code
Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers
With this paper, we aim to provide a primer to the astronomical community, including authors, reviewers, and editors, on how to implement machine learning models and report their results in a way that ensures the accuracy of the results, reproducibility of the findings, and usefulness of the method.
The Fornax3D project: Assembly histories of lenticular galaxies from a combined dynamical and population orbital analysis
Comparing the derived assembly histories with a comparable galaxy in a low-density environment -- NGC 3115 -- we find evidence for cluster-driven suppression of stellar accretion and merging.
Astrophysics of Galaxies
Fornax 3D project: automated detection of planetary nebulae in the centres of early-type galaxies and first results
Finally, we test the reliability and robustness of our novel detection and analysis method.
Ranked #1 on
Object Detection
on Extragalactic Planetary Nebulae
Object Detection
Astrophysics of Galaxies
