Report  Open Access

CNR activity in the ESA Extension project

Vairo C., Bolettieri P., Gennaro C., Amato G.

Visual recognition  Artificial Intelligence  Computer vision  Deep Learning  Cultural Heritage 

The CNR activity within the ESA "EXTENSION" project aims to develop an advanced visual recognition system for cultural heritage objects in L'Aquila, using AI techniques such as classifiers. However, this task requires substantial computational resources due to the large amount of data and deep learning-based AI techniques involved. To overcome these challenges, a centralized approach has been adopted, with a central server providing the necessary computational power and storage capacity.

Source: ISTI Technical Report, ISTI-TR-2023/010, pp.1–10, 2023


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BibTeX entry
	title = {CNR activity in the ESA Extension project},
	author = {Vairo C. and Bolettieri P. and Gennaro C. and Amato G.},
	doi = {10.32079/isti-tr-2023/010},
	institution = {ISTI Technical Report, ISTI-TR-2023/010, pp.1–10, 2023},
	year = {2023}