Road green belt trimming task automatic generation method based on neural network and CIM

Abstract

The invention provides a road green belt trimming task automatic generation method based on a neural network and a CIM, and the method comprises the steps: carrying out the collection of an RGB imageof a green belt through a road camera, transmitting the RGB image to a semantic segmentation network, outputting a semantic segmentation image, taking the semantic segmentation image as a mask, carrying out the trimming operation of the RGB image, and obtaining a green belt image; and performing post-processing on the green belt image to obtain a texture feature map, sending the texture feature map to a texture classification network, outputting a texture clutter level of the green belt after processing, storing an output result of the texture classification network in a CIM, and generating acorresponding green belt trimming task according to the output clutter level. According to the method, the messy situation of the road green belt can be objectively and accurately judged, and a greenbelt trimming task is automatically generated to remind related department managers to trim the green belt in time.

Description

technical field [0001] The invention relates to the fields of artificial intelligence and smart cities, in particular to a method for automatically generating road green belt pruning tasks based on neural networks and CIM. Background technique [0002] If the urban green belt is not pruned in time when it grows naturally, the phenomenon of closed canopy and dense branches will often appear, which not only affects the city appearance, but also affects people's traffic. At present, the pruning period of the green belt needs to be judged manually, and the use of manual observation, on the one hand, the labor intensity of the observers is high, on the other hand, due to factors such as tight manpower, high cost, and human cognition, it will lead to inaccurate information and omissions. phenomenon occurs. Contents of the invention [0003] In order to solve the above problems, the present invention proposes a method for automatic generation of road green belt pruning tasks bas...

AI Technical Summary

Problems solved by technology

[0002] If the urban green belt is not pruned in time when it grows naturally, the phenomenon of closed canopy and dense branches will often appear, which will not only affect the city appearance, but also affect people's traffic

At present, the pruning period of the green belt needs to be judged manually, and the use of manual observation, on the one hand, the labor intensity of the observers is high, on the other hand, due to factors such as tight manpower, high cost, and human cognition, it will lead to inaccurate information and omissions. phenomenon occurs

Images