Research on Pavement Distress Recognition Method Based on YOLOv8
Automatic recognition of pavement damage is a research hotspot in the field of road maintenance,and how to improve the automatic recognition rate and accuracy of pavement damage is the focus of researchers.In this paper,the YOLOv8 model is used to identify pavement disease.This method uses the YOLOv8 model to train the data set after image pretreatment and generate a training model to identify pavement disease images.The experimental results show that the de-tection accuracy of this method is 94.6%the model performance index F1 value is 0.94,and the recognition effect is good.
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