Logistics vehicle feature positioning method based on improved faster R-CNN

Abstract

The invention discloses a logistics vehicle feature positioning method based on an improved faster R-CNN. The method comprises the steps of 1, enhancing logistics vehicle images by introducing a dataenhancement means to process a logistics vehicle image; 2, constructing a basic network model in which a VGGNet-16 basic network is adopted as a feature extraction network; meanwhile, in order to realize positioning of logistics vehicles, a target detection positioning model of an RPN network is added behind a feature extraction module in a third convolution layer of a fifth convolution layer of the VGGNet-16; 3, screening logistics vehicle targets by using a non-maximum suppression algorithm; and 4, performing unified normalization on the logistics vehicle target features, and transmitting the obtained feature map of the fixed dimension data to the seventh stage of the basic network model, so that the accurate probability of the logistics vehicle positioning bounding box and the corresponding vehicle type can be obtained. According to the method, the feature positioning performance of the logistics vehicle is good in different environments and scenes.

Description

technical field [0001] The invention relates to a method for feature location of logistics vehicles based on improved faster R-CNN. [0002] technical background [0003] In recent years, with the development of transportation and logistics, more and more logistics vehicles serve our work and life, but this has also caused a problem. Too many logistics engineering vehicles have made parking management in the park more difficult. . Although operations such as towing and hanging of logistics vehicles can improve the operational efficiency of cargo loading, there are still problems such as unreasonable occupation of parking spaces by logistics vehicles, and the inability to charge accurately for towing and hanging. There are extremely dangerous behaviors such as card decks in avoiding the detection of monitoring. [0004] In order to effectively solve the management problems of logistics engineering vehicles, there are many examples of identifying logistics vehicles of differe...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides a method based on improved faster R-CNN for the management problems of logistics engineering v

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