Search Results for author: S. Riggi

Found 5 papers, 1 papers with code

Classification of compact radio sources in the Galactic plane with supervised machine learning

no code implementations23 Feb 2024 S. Riggi, G. Umana, C. Trigilio, C. Bordiu, F. Bufano, A. Ingallinera, F. Cavallaro, Y. Gordon, R. P. Norris, G. Gürkan, P. Leto, C. Buemi, S. Loru, A. M. Hopkins, M. D. Filipović, T. Cecconello

To this aim, we produced a curated dataset of ~20, 000 images of compact sources of different astronomical classes, obtained from past radio and infrared surveys, and novel radio data from pilot surveys carried out with the Australian SKA Pathfinder (ASKAP).

Pathfinder

Astronomical source finding services for the CIRASA visual analytic platform

no code implementations15 Oct 2021 S. Riggi, C. Bordiu, F. Vitello, G. Tudisco, E. Sciacca, D. Magro, R. Sortino, C. Pino, M. Molinaro, M. Benedettini, S. Leurini, F. Bufano, M. Raciti, U. Becciani

Innovative developments in data processing, archiving, analysis, and visualization are nowadays unavoidable to deal with the data deluge expected in next-generation facilities for radio astronomy, such as the Square Kilometre Array (SKA) and its precursors.

Astronomy Data Visualization

Astronomical research in the next decade: trends, barriers and needs in data access, management, visualization and analysis

no code implementations14 Dec 2020 C. Bordiu, F. Bufano, E. Sciacca, S. Riggi, M. Molinaro, G. Vizzari, M. Krokos, C. Brandt

We report the outcomes of a survey that explores the current practices, needs and expectations of the astrophysics community, concerning four research aspects: open science practices, data access and management, data visualization, and data analysis.

Data Visualization Instrumentation and Methods for Astrophysics

CAESAR source finder: recent developments and testing

1 code implementation13 Sep 2019 S. Riggi, F. Vitello, U. Becciani, C. Buemi, F. Bufano, A. Calanducci, F. Cavallaro, A. Costa, A. Ingallinera, P. Leto, S. Loru, R. P. Norris, F. Schillirò, E. Sciacca, C. Trigilio, G. Umana

Given the increased scale of the data, source extraction and characterization, even in this Early Science phase, have to be carried out in a mostly automated way.

Pathfinder

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