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Il “terzo pacchetto” di modifiche al regolamento della Camera: una riforma ampia e complessivamente equilibrata

ML Approaches for the Study of Significant Heritage Contexts: An Application on Coastal Landscapes in Sardinia

Remote Sensing (RS) and Geographic Information Science (GIS) techniques are powerful tools for spatial data collection, analysis, management, and digitization within cultural heritage frameworks. Despite their capabilities, challenges remain in automating data semantic classification for conservation purposes. To address this, leveraging airborne Light Detection And Ranging (LiDAR) point clouds, complex spatial analyses, and automated data structuring is crucial for supporting heritage preser...

An application of a reality-based approach for the generation of masonry cross vaults FE block models

In recent years, the synergy between Geomatics and Structural Engineering has opened new frontiers in the analysis of the built heritage. In particular, the possibility of using reality-based models as starting data to develop structural models has become increasingly appealing to take into account some aspects that are usually neglected in the analysis of historical masonry constructions, such as the as-built deformed geometry and the block arrangement. The proposed approach is based on an i...

Traditional and New Sensing Techniques Combination for the Identification of the Forgotten “New Flour-Weighing House” in Valencia, Spain

In the city of Valencia (Spain), there existed from the Middle Ages until the mid-nineteenth century a building that fulfilled a municipal strategic function: The “new flour-weighing house”. Its purpose was to distribute food to the population and collect the corresponding indirect municipal taxes. Today, the existence of this building is not remembered, neither by scientists nor by citizens, and its importance, location and appearance are unknown. The building investigated, behind which the ...

Synthetic Training Datasets for Architectural Conservation: A Deep Learning Approach for Decay Detection

Architectural heritage conservation increasingly relies on innovative tools for detecting and monitoring degradation. The study presented in the current paper explores the use of synthetic datasets—namely, rendered images derived from photogrammetric models—to train convolutional neural networks (CNNs) for the automated detection of deterioration in historical reinforced concrete structures. The primary objective is to assess the effectiveness of synthetic images for deep learning training, c...

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