Research on pavement crack identification method based on convolution neural network
WANG Si-yuan
LIU Jie
Abstract：This paper takes pavement cracks as the research object,uses semantic segmentation algorithm as the main tool to identify them,and analyzes the preprocessing of pavement cracks image,the expansion of data set,and the improvement of classical UNet network model.To determine the optimal depth of UNet network,extensive network architecture search or inefficient integration test is needed.MobileNetV3 network is proposed to replace the encoder part of UNet for feature extraction,which improves the effect and speed.Compared with the classical UNET model,the improved UNET-MobileNetV3 network model has fewer parameters,shorter running time,and a more optimized structure.The identification of cracks has been successfully completed,which provides a new idea for road maintenance.
Keywords：pavement cracksdeep learaningsemantic segmentationUNet neural network
Publication Date：2023-12-28
Pages：5( 18-22 )