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.

CNR activity in the ESA Extension project

Vairo C;Bolettieri P;Gennaro C;Amato G
2023

Abstract

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.
2023
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Visual recognition
Artificial Intelligence
Computer vision
Deep Learning
Cultural Heritage
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/456664
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