Artificial Intelligence for digital REStoration of Cultural Heritage (AIRES-CH) aims at building a web-based app for the digital restoration of pictorial artworks through Computer Vision technologies applied to physical imaging raw data. Physical imaging techniques, such as XRF, PIXE, PIGE, and FTIR, are capable of exploring a wide range of wavelengths providing spectra that are used to infer the chemical composition of the pigments. A multidimensional neural network, specifically designed to automatically restore damaged or hidden pictorial work, will be deployed on the INFN-CHNet Cloud as a web service, freely available to authenticated researchers. In this contribution, we report the status of the project, its current results, the development plans as well as future prospects.

The AIRES-CH Project: Artificial Intelligence for Digital REStoration of Cultural Heritages Using Nuclear Imaging and Multidimensional Adversarial Neural Networks / Bombini, Alessandro; Anderlini, Lucio; dell'Agnello, Luca; Giaocmini, Francesco; Ruberto, Chiara; Taccetti, Francesco. - ELETTRONICO. - 13231:(2022), pp. 685-700. ( 21st International Conference on Image Analysis and Processing, ICIAP 2022 ita 2022) [10.1007/978-3-031-06427-2_57].

The AIRES-CH Project: Artificial Intelligence for Digital REStoration of Cultural Heritages Using Nuclear Imaging and Multidimensional Adversarial Neural Networks

Anderlini, Lucio;Ruberto, Chiara;
2022

Abstract

Artificial Intelligence for digital REStoration of Cultural Heritage (AIRES-CH) aims at building a web-based app for the digital restoration of pictorial artworks through Computer Vision technologies applied to physical imaging raw data. Physical imaging techniques, such as XRF, PIXE, PIGE, and FTIR, are capable of exploring a wide range of wavelengths providing spectra that are used to infer the chemical composition of the pigments. A multidimensional neural network, specifically designed to automatically restore damaged or hidden pictorial work, will be deployed on the INFN-CHNet Cloud as a web service, freely available to authenticated researchers. In this contribution, we report the status of the project, its current results, the development plans as well as future prospects.
2022
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
21st International Conference on Image Analysis and Processing, ICIAP 2022
ita
2022
Bombini, Alessandro; Anderlini, Lucio; dell'Agnello, Luca; Giaocmini, Francesco; Ruberto, Chiara; Taccetti, Francesco
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1462694
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