Soluzioni di Machine Learning per il Patrimonio Culturale. Il progetto ArtI4EO.

Abstract

Through ArtI4EO, the Project Team
wanted to explore the possible use
of neural networks based on ML
techniques applied to satellite, photographic
and UAV image datasets,
i) for a more in-depth description
of the context in which an archaeological
asset is located and ii) for
the characterization of some types
of damage present on the surface of
the assets. The use of Machine Learning
and Deep Learning techniques
in the context of monitoring and
safeguarding cultural heritage constitutes
an important technological
advancement. In particular, having
automatic tools and methodologies
for identifying damage constitutes
a strategic asset of considerable
importance, especially if applied to
the Italian context characterized by
an incredible widespread archaeological
and architectural heritage.