1 citations · 2 across the 7 of their papers we have counts for
3 papers · 1 filter
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…
Generalizability analysis of deep learning predictions of human brain responses to augmented and semantically novel visual stimuli
Valentyn Piskovskyi, Riccardo Chimisso, Sabrina Patania +3
The purpose of this work is to investigate the soundness and utility of a neural network-based approach as a framework for exploring the impact of image enhancement techniques on v…
Sifting the debris: Patterns in the SNR population with unsupervised ML methods
F. Bufano, C. Bordiu, T. Cecconello +13
Supernova remnants (SNRs) carry vast amounts of mechanical and radiative energy that heavily influence the structural, dynamical, and chemical evolution of galaxies. To this day, m…