Aiming at the problems of insufficient data,low Detection accuracy and missed detection of aerial images of asphalt pavement,an improved DETR(Detection Transformer)end-to-end asphalt pavement damage detection model is proposed.Firstly,the model uses ResNet50 to extract features,introduces the SiLU activation function to improve feature extraction ability,and uses a multi-scale fusion feature map to retain more context semantic information.Sec-ondly,the multi-scale deformable self-attention mechanism is used in the Transformer Encoder to accelerate the con-vergence speed of the model.Finally,the CIoU loss function is used to improve the accuracy of crack detection.The ex-perimental results show that the average precision of the improved model is 83.7%,which is 7.4%higher than that of the DETR model,and the recall rate is increased by 10.9%.The proposed improved model can effectively detect as-phalt pavement damage,which can provide a reference for the detection of asphalt pavement damage in aerial images.
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