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This study presents a novel approach using convolutional neural networks to fuse infrared thermography and microwave technology for assessing moisture damage in cultural heritage buildings, specifically the Yungang Grottoes in China. By combining data from these non-destructive techniques, the research aims to accurately diagnose moisture distribution and quantify damage, enhancing conservation efforts. The findings demonstrate the effectiveness of this multimodal image fusion in identifying and evaluating

Author

Mani Shankar

Language

EN