道路裂纹检测的神经网络算法研究

Yuxiang Liu, Wei She, Shuai Tan
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引用次数: 0

摘要

针对道路裂纹检测问题,开展了基于CFD数据集和Unet模型的路面裂纹检测实验。分析了网络的总体结构以及各模块对Unet模型最终检测效果的贡献。在此基础上对Unet模型中的部分模块进行了切割和替换,得到了CCUnet模型。最后的实验结果表明,在基本保持模型精度的情况下,CCUnet模型的检测率得到了很大的提高,具有实际应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Neural Network Algorithm for Road Crack Detection
Aiming at the problem of road crack detection, experiments based on CFD data set and Unet model were carried out. The overall structure of the network and the contribution of each module to the final detection effect of Unet model were analyzed. Some modules in Unet model were cut and replaced based on that, and CCUnet model was obtained. Final experiment results show that detection rate of CCUnet model is greatly improved under the condition that model accuracy is maintained basically, and that has practical application value.
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