[6] [6] Zheng Tong,Jie Gao,Zhenqiang Han,et al. Recognition of asphalt pavement crack length using deep convolutional neural networks[J]. Road Materials and Pavement Design,2018,19(6):17-20.

[7] [7] Lim SeMin,Jun SangWoo. MobileNets Can Be Lossily Compressed:Neural Network Compression for Embedded Accelerators[J]. Electronics,2022,11(6):103-105.

[8] [8] Woo Sanghyun et al. CBAM: Convolutional Block Attention Module[M]. Springer International Publishing, 2018: 3-19.

[9] [9] Liu Songtao, Huang Di, Wang Yunhong. Receptive Field Block Net for Accurateand Fast Object Detection [ M]. Springer International Publishing, 2018: 404-419.

[10] [10] He Kaiming,Zhang Xiangyu,Ren Shaoqing,et al. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition. [J]. IEEE transactions on pattern analysis and machine intelligence,2015,37(9):11-18.

[11] [11] Bochkovskiy A, Wang C Y, Liao H. YOLOv4: Optimal Speed and Accuracy of Object Detection[J]. Electronics,2020, 57(5):4254-4258.

[12] [12] Wang C Y, Liao, H Y M, Wu Y H, et al. CSPNet: A new backbone that can enhance learning capability of CNN[C] / / Proceedings of the IEEE/ CVF Conference on Computer Vision and Pattern Recognition Workshops. USA:IEEE,2020:390-391.

[14] [14] Li Guo,Runze Li,Bin Jiang, et al. Automaticcrack distress classification from concrete surface images using a novel deep - width network architecture [ J]. Neurocomputing,2020, 397: 383-392.

[15] [15] Hongyan Xu,Xiu Su,Yi Wang, et al. Automatic Bridge Crack Detection Using a Convolutional Neural Network[J].Applied Sciences, 2019, 9(14):27-32.