东南大学学报（英文版）2023，Vol.39Issue(4)：393-399,7.DOI:10.3969/j.issn.1003-7985.2023.04.008
基于SSD及剪枝神经网络的复杂环境下混凝土裂缝识别
Concrete crack identification in complex environments based on SSD and pruning neural network
摘要
Abstract
To solve the problem of poor crack identification algorithm performance in complex environments,an improved method based on a single-shot multibox detector(SSD)algorithm was proposed.This method realized high-precision crack identification for crack images with added noise by adjusting the combination of the number of different resolution prior bounding boxes in the original SSD algorithm.A sufficient number of crack images were captured and preprocessed in actual scenes and laboratories,and noise was added to the crack dataset using a pretzel algorithm to simulate the crack images in complex environments.The improved method was tested along with the original SSD algorithm to identify the crack dataset,and their test results were compared.The results show that the crack identification accuracy of the original SSD algorithm and improved method decreases with increasing noise levels.When a 20％grade of pretzel noise is added at high density,the accuracy in recognizing cracks is 31.7％and 93.0％for the original SSD algorithm and the improved method,respectively.Therefore,the improved method has excellent antinoise ability and can be used for crack identification in complex environments.关键词
裂缝识别/剪枝神经网络/图像加噪/抗噪性能/病害检测Key words
crack identification/pruned neural network/image noise addition/antinoise performance/disease detection分类
信息技术与安全科学引用本文复制引用
王燕华,何俊泽,张明洲,戴博闻,徐浩然..基于SSD及剪枝神经网络的复杂环境下混凝土裂缝识别[J].东南大学学报（英文版）,2023,39(4):393-399,7.基金项目
The National Major Scientific Research Instrument Development Project(No.11827801),the National Science and Tech-nology Project(No.2020YFC1511904). （No.11827801）
