An end-to-end deep learning framework for structural damage assessment using semantic segmentation and point cloud analysis
The necessity for automated post-disaster building damage analysis using deep learning techniques arises from the critical need for rapid and accurate damage assessment following natural disasters. Traditional manual survey methods are time-consuming, labor-intensive, and potentially hazardous to gr...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025026246 |
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