Deep Learning-Based Framework for Damage Introduction and Its Segmentation in Ancient Mural Paintings

Puntos clave

• Damage segmentation in ancient mural paintings enhances preservation efforts, addressing restoration needs.
• The framework utilizes deep learning methods to accurately segment and analyze damage patterns in murals.
• Assessment involves advanced image processing techniques, focusing on the intricacies of aging artwork.
• Findings may inform future approaches to conserving valuable cultural heritage artifacts.