Building Surface Crack Detection Using Deep Learning Technology
Problem
Cracks in building facades worsen if not found quickly, and manual inspection of large buildings is impractical, motivating automated crack detection.
Why it matters
Undetected facade cracks can exacerbate structural deterioration and raise maintenance and safety costs.
What the AI did
The study investigated the effectiveness of deep learning, specifically CNN-based image classification, for detecting cracks in building facades, while addressing the difficulty of collecting large training datasets.
Results
not stated in source
Impact
The study explores deep learning for facade crack detection, but the abstract states no measured performance.
Record
| Venue | Buildings |
|---|---|
| Published | 2023 |
| Work type | article |
| Authors | Yulong Chen, Zilong Zhu, Zhijie Lin, Youmei Zhou |
| Citations | 46 (OpenAlex, at import time) |
| References | 26 |
| Model or method | Convolutional Neural Networks (CNN) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/buildings13071814 |
| Open access | gold |
| Keywords | deep learning, CNN, crack detection, building facades, image classification, inspection |
Importance rating
real but narrower advance
Automating facade crack inspection addresses building safety and maintenance costs, but abstract gives no scale or impact figures.
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