A neural network-based road disease identification method and device

Abstract

The embodiment of the invention provides a road disease identification method and device based on a neural network. The method comprises the following steps of: obtaining a sample; obtaining a road disease image sent by vehicle-mounted collection equipment, inputting the road disease image into a preset convolutional neural network model, calculating to obtain a disease category value corresponding to the road disease image; the disease relative position and the disease instance are divided into regions; wherein the disease relative position is the position of the disease in the road disease image; determining a disease category corresponding to the road disease image according to the disease category value, determining a disease level corresponding to the road disease image according to the disease relative position or the disease instance segmentation area, The disease category and the disease grade can be automatically identified through the disease image, the identification efficiency is high, the identification accuracy can be improved through the preset convolutional neural network model, and the problems of low manual identification efficiency and potential safety hazards are avoided.

Description

technical field [0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a neural network-based road disease identification method and device. Background technique [0002] With the continuous improvement of our country's traffic construction, road traffic occupies an important position in our country's economy and people's life. However, with the construction of roads, later maintenance has become the main problem. How to quickly find problems and take measures when road diseases appear can greatly save road maintenance costs. Therefore, without affecting the normal traffic order, the entire section can be repaired quickly Identifying roadside diseases and locating problem areas has become a major problem that needs to be solved urgently. [0003] At present, the traditional method of identifying road diseases is mainly through manual on-site inspection, that is, during the regular road maintenance process, road maint...

AI Technical Summary

Problems solved by technology

[0004] However, the inventor found the following problems in the existing way of manually identifying road diseases: the efficiency of manual investigation is low, and there are great hidden dangers to the personal safety of road maintenance personnel

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