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 (CN...

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Bibliographic Details
Main Authors: Giacomo Patrucco, Francesco Setragno, Antonia Spanò
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/17/10/1714
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