Crack U-Net:Towards High Quality Pavement Crack Detection

• Published in: Ji suan ji ke xue Vol. 49; no. 1; pp. 204 - 211
• Main Authors: Zhu, Yi-fan, Wang, Hai-tao, Li, Ke, Wu, He-jun
• Format: Journal Article
• Language: Chinese
• Published: Chongqing Guojia Kexue Jishu Bu 01.01.2022; Editorial office of Computer Science
• Subjects: Accuracy; Coders; Convolution; Datasets; Electronic devices; Encoders-Decoders; Feature extraction; Flaw detection; Image segmentation; Pavements; road pavement|crack detection|deep learning|image segmentation; Scale models; Vehicle safety

Pavement cracks have a great potential threat to driving safety, and the previous manual detection methods are not efficient. The existing crack detection methods have low model generalization ability, poor crack segmentation ability and low efficiency in complex backgrounds. In order to solve these...