17 citations · 58 across the 20 of their papers we have counts for
4 papers · 1 filter
Self-supervised contrastive learning of radio data for source detection, classification and peculiar object discovery
S. Riggi, T. Cecconello, S. Palazzo +14
New advancements in radio data post-processing are underway within the SKA precursor community, aiming to facilitate the extraction of scientific results from survey images through…
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…
Astronomical source detection in radio continuum maps with deep neural networks
S. Riggi, D. Magro, R. Sortino +13
Source finding is one of the most challenging tasks in upcoming radio continuum surveys with SKA precursors, such as the Evolutionary Map of the Universe (EMU) survey of the Austra…
Automated detection of extended sources in radio maps: progress from the SCORPIO survey
S. Riggi, A. Ingallinera, P. Leto +7
Automated source extraction and parameterization represents a crucial challenge for the next-generation radio interferometer surveys, such as those performed with the Square Kilome…