Research on Modified Vehicle Identification Technology Based on YOLO V5
With the continuous rise of car ownership in China,some users pursue personalization to modify their vehicles,and some truck drivers modify their vehicles to increase the transportation volume,etc.,which brings a great impact on road traffic safety,and in order to solve the problem of illegal modified vehicle identification,the article researches the modified vehicle identification technology.This study takes YOLO V5 as the model base,replaces the backbone feature extraction network with highly flexible and easy-to-implement MobileNet V2,and replaces all the conventional convolution operations in the reinforcement feature extraction network with depth separable convolution.Finally,a detection model for illegally modified vehicles with high detection efficiency,small computational requirements and fast detection speed is obtained.
YOLO V5identification of modified vehiclesvehicle detection technology
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