Protecting Historical Treasures: Deep Learning for Structural Health Assessment

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Research demonstrates deep learning's efficacy in detecting cracks and moss in ancient monuments, highlighting preservation efforts.

Effective deep learning models achieved detection accuracies of 96.9% for cracks and 97.5% for moss, indicating high performance.
Utilizing high-resolution images from the dataset Indian Ancient Monuments, algorithms enhance structural health assessment.
The approach employs the Single Shot Multibox Detector (SSD), outperforming traditional methods like SVM and Random Forest.
The findings support proactive cultural heritage conservation, enabling real-time monitoring for preservation authorities.

Snehapriya et al. (2025) studied this question.

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