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20242026
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astro-ph.IM20262 cited

iDaVIE v1.0: A virtual reality tool for interactive analysis of astronomical data cubes

Alexander Sivitilli, Lucia Marchetti, Angus Comrie +10

As modern astronomy confronts unprecedented data volumes, automated pipelines and machine-learning techniques have become essential for processing and analysis. As these workflows…

astro-ph.IM2025

Solar flare forecasting with foundational transformer models across image, video, and time-series modalities

S. Riggi, P. Romano, A. Pilzer +1

We present a comparative study of transformer-based architectures for solar flare forecasting using heterogeneous data modalities, including images, video sequences, and time-serie…

astro-ph.IM2025

From Local to Remote: VisIVO Visual Analytics in the Era of the Square Kilometre Array

Giuseppe Tudisco, Fabio Vitello, Eva Sciacca +1

The field of astrophysics is continuously advancing, with an ever-growing influx of data requiring robust and efficient analysis tools. As the Square Kilometre Array (SKA) radio te…

astro-ph.IM2025

The Gaia AVU-GSR solver: a CPU + GPU parallel code toward Exascale systems

Valentina Cesare, Ugo Becciani, Alberto Vecchiato +3

The solver module of the Astrometric Verification Unit - Global Sphere Reconstruction (AVU-GSR) pipeline aims to find the astrometric parameters of stars in the Milky…

astro-ph.IM2024

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

Detection and classification of radio sources with deep learning

S. Riggi, T. Cecconello, U. Becciani +1

In this paper we present three different applications, based on deep learning methodologies, that we are developing to support the scientific analysis conducted within the ASKAP-EM…