Laser & Optoelectronics Progress, Volume. 62, Issue 10, 1012002(2025)
Pavement Crack Segmentation Detection Integrating Multiple Attention Mechanisms
[1] Weng P, Lu Y H, Qi X B et al. Pavement crack segmentation technology based on improved fully convolutional networks[J]. Computer Engineering and Applications, 55, 235-239, 245(2019).
[3] Oliveira H, Correia P L. Automatic road crack segmentation using entropy and image dynamic thresholding[C], 622-626(2009).
[5] Fu Q, Bu F M, Ren H P et al. Pavement crack target detection based on deep learning method[J]. Highway, 68, 395-405(2023).
[6] Chen B, He S, Liu J et al. Weld structured light image segmentation based on lightweight DeepLab v3+network[J]. Chinese Journal of Lasers, 50, 0802105(2023).
[10] Zhang M X, Xu J, Liu X P et al. Improved U-Net pavement crack detection method[J]. Computer Engineering and Applications, 60, 306-313(2024).
[11] Xia X H, Su J G, Wang Y Y et al. Lightweight pavement crack detection model based on DeepLabv3+[J]. Laser & Optoelectronics Progress, 61, 0812001(2024).
[13] Liao Z H, Zhang Y C, Yang B et al. Monocular height estimation method of remote sensing image based on Swin Transformer-CNN and its application in highway road construction sites[J]. Acta Gieodaetica et Cartographica Sinica, 53, 344-352(2024).
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Pengfei Gao, Liya Zhang, Yukun Wang, Lin Zhang. Pavement Crack Segmentation Detection Integrating Multiple Attention Mechanisms[J]. Laser & Optoelectronics Progress, 2025, 62(10): 1012002
Category: Instrumentation, Measurement and Metrology
Received: Sep. 30, 2024
Accepted: Nov. 26, 2024
Published Online: Apr. 25, 2025
The Author Email: Liya Zhang (lyzhang47@sina.com)
CSTR:32186.14.LOP242068