Deep Convolutional Neural Network and Its Application in Image Recognition of Road Safety Projects

摘要

Road safety projects constitute an important part of road safety facilities. Assessing the safety of these projects is important for assessing the safety of roads. In recent years, road safety problems have caused enormous losses to the country and its people. Traditional inspection and maintenance of road safety projects mainly involve manual inspection and on-site maintenance: however, manual inspection is time-consuming and laborious, and it cannot be used to identify safety issues in large areas. This paper focuses on the application of the deep convolutional neural network algorithm, a deep learning algorithm, for the recognition of road safety projects. Comparative analysis of the experimental results shows that both the convolutional neural network models VGG16 and Inception V3 can identify the pre-processed data sets of the road safety projects; however, the accuracy of the test set model Inception V3 is higher than that of VGG16, reaching 93.3%.