Design and implementation of building crack detection system based convolutional neural network

Hedan Liu; Xulei Zhao

doi:10.1117/12.2653463

8 December 2022 Design and implementation of building crack detection system based convolutional neural network

Hedan Liu, Xulei Zhao

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124741Y (2022) https://doi.org/10.1117/12.2653463
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

Buildings are commonly found as important facilities in today's society. How to detect building cracks safely and effectively is a necessary measure to ensure the safety of people's lives and properties. With the emergence of deep learning algorithms, various target detection methods based on convolutional neural network (CNN) models have gradually replaced conventional manual detection methods. In this paper, we design a crack recognition system based on convolutional neural network model for building images collected by UAVs. The experimental structure shows that the system has a good performance and can be further promoted to be applied in the field of safety assessment in the construction industry.

Citation Download Citation

Hedan Liu and Xulei Zhao "Design and implementation of building crack detection system based convolutional neural network", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124741Y (8 December 2022); https://doi.org/10.1117/12.2653463

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