activity
20172024
most citedA hybrid supervised/unsupervised machine learning approach to solar flare prediction

83 citations · 210 across the 14 of their papers we have counts for

collaborators

16 papers

astro-ph.SR2024

AI-FLARES: Artificial Intelligence for the Analysis of Solar Flares Data

Michele Piana, Federico Benvenuto, Anna Maria Massone +6

AI-FLARES (Artificial Intelligence for the Analysis of Solar Flares Data) is a research project funded by the Agenzia Spaziale Italiana and by the Istituto Nazionale di Astrofisica…

math.NA2023

Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images

Giulio Paolucci, Isabella Cama, Cristina Campi +1

The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia, i.e. a systemic loss of skeletal muscle mass an…

cs.LG2023

A comprehensive theoretical framework for the optimization of neural networks classification performance with respect to weighted metrics

Francesco Marchetti, Sabrina Guastavino, Cristina Campi +2

In many contexts, customized and weighted classification scores are designed in order to evaluate the goodness of the predictions carried out by neural networks. However, there exi…

astro-ph.SR2022★ 1 cited

Operational solar flare forecasting via video-based deep learning

Sabrina Guastavino, Francesco Marchetti, Federico Benvenuto +2

Operational flare forecasting aims at providing predictions that can be used to make decisions, typically at a daily scale, about the space weather impacts of flare occurrence. Thi…

astro-ph.SR2021★ 33 cited

Implementation paradigm for supervised flare forecasting studies: a deep learning application with video data

Sabrina Guastavino, Francesco Marchetti, Federico Benvenuto +2

Solar flare forecasting can be realized by means of the analysis of magnetic data through artificial intelligence techniques. The aim is to predict whether a magnetic active region…

astro-ph.SR2021★ 1 cited

The Flare Likelihood and Region Eruption Forecasting (FLARECAST) Project: Flare forecasting in the big data & machine learning era

M. K. Georgoulis, D. S. Bloomfield, M. Piana +25

The EU funded the FLARECAST project, that ran from Jan 2015 until Feb 2018. FLARECAST had a R2O focus, and introduced several innovations into the discipline of solar flare forecas…