1 citations · 1 across the 3 of their papers we have counts for
3 papers
astro-ph.IM2024★ 1 cited
Self-supervised learning for radio-astronomy source classification: a benchmark
Thomas Cecconello, Simone Riggi, Ugo Becciani +5
The upcoming Square Kilometer Array (SKA) telescope marks a significant step forward in radio astronomy, presenting new opportunities and challenges for data analysis. Traditional…
astro-ph.IM2024
Classification of compact radio sources in the Galactic plane with supervised machine learning
S. Riggi, G. Umana, C. Trigilio +13
Generation of science-ready data from processed data products is one of the major challenges in next-generation radio continuum surveys with the Square Kilometre Array (SKA) and it…
astro-ph.IM2023
Radio source analysis services for the SKA and precursors
Simone Riggi, Cristobal Bordiu, Daniel Magro +8
New developments in data processing and visualization are being made in preparation for upcoming radioastronomical surveys planned with the Square Kilometre Array (SKA) and its pre…