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<citation_list><citation key="ref0"><unstructured_citation>Rizvi Aliza Raza, Khan Pervez Rauf., Ahmad Shafeeq., 2016, &quot;Crack Detection in Railway Track using Image Processing,&quot; International Journal of Advance Research, Technology Ideas and Inventions., 3(4), pp. 489-496.</unstructured_citation></citation><citation key="ref1"><doi>10.1109/TIM.2015.2509278</doi><unstructured_citation>Romulo Gonçalves Lins and Sidney N. Givigi., 2016, &quot;Image Analysis-based Automated Crack Detection and Calculation&quot;, IEEE Instrumentation and Measurement Transactions., 65(3), pp.583-590.</unstructured_citation></citation><citation key="ref2"><doi>10.1109/TITS.2016.2552248</doi><unstructured_citation>Yong Shi., Limeng Cui., Zhiquan Qi., Fan Meng., and Zhensong Chen., 2016, &quot;Automatic Road Crack Detection using Random Structured Forests,&quot; IEEE Transactions on Intelligent Transportation Systems., 17, pp. 3434 - 3445.</unstructured_citation></citation><citation key="ref3"><doi>10.1109/TITS.2015.2477675</doi><unstructured_citation>Rabih Amhaz., Sylvie Chambon., Jerome Idier and Vincent Baltazart., 2016, &quot;Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm based on Minimal Path Selection&quot;, IEEE Transactions on Intelligent Transportation Systems 17, pp. 2718 - 2729.</unstructured_citation></citation><citation key="ref4"><doi>10.1061/(ASCE)CP.1943-5487.0000447</doi><unstructured_citation>Mojtaba Kamaliardakani., Lu Sun and Mostafa K. Ardakani., 2016, &quot;Sealed-Crack Detection Algorithm using Heuristic Thresholding Approach&quot;, Journal of Computing in Civil Engineering., 30</unstructured_citation></citation><citation key="ref5"><unstructured_citation>Nouha Ben Cheikh Ahmed., Samer Lahouar., Chokri Souani., Kamel Besbes., 2017, &quot;Automatic Crack Detection from Pavement Images using Fuzzy Thresholding&quot;, International Conference on Control, Automation and Diagnosis., pp. 528 - 537.</unstructured_citation></citation><citation key="ref6"><doi>10.3390/s141019307</doi><unstructured_citation>Wenyu Zhang., Zhenjiang Zhang.,Dapeng Qi and Yun Liu., 2014, &quot;Automatic Crack Detection and Classification Method for Subway Tunnel Safety Monitoring,&quot; Sensors., ISSN. 1424 - 8220, pp. 19307-19328.</unstructured_citation></citation><citation key="ref7"><doi>10.1016/j.cemconres.2017.04.018</doi><unstructured_citation>H. Kim, E. Ahn, S. Cho, M.Shin, and S.-H.Sim, &quot;Comparative analysis of image binarization methods for crack identification in concrete structures,&quot; Cement and Concrete Research, vol. 99, pp. 53-61, 2017.</unstructured_citation></citation><citation key="ref8"><doi>10.1016/j.protcy.2015.02.008</doi><unstructured_citation>K. Khalili and M. Vahidnia, &quot;Improving the accuracy of crack length measurement using machine vision&quot;, ProcediaTechnol., vol. 19, pp. 48-55, Oct. 2015.</unstructured_citation></citation><citation key="ref9"><unstructured_citation>Dapeng Qi1, Yun Liu1, Qingyi Gu, Fengxia Zheng An algorithm to detect the crack in the tunnel based on the image processing J. Comput., 26 (3) (2015)</unstructured_citation></citation><citation key="ref10"><unstructured_citation>Paul Zheng, Cristopher D. MoenCrack detection and measurement are utilizing image-based reconstruction Struct. Eng. Mater. (2014)</unstructured_citation></citation><citation key="ref11"><doi>10.1007/s11265-013-0813-8</doi><unstructured_citation>H.N. Nguyen, T.Y. Kam, P.Y. Cheng An automatic approach for accurate edge detection of concrete crack utilizing 2D geometric features of crack J. Signal Process. Syst. (2013), pp. 1-20</unstructured_citation></citation><citation key="ref12"><doi>10.3390/s141019307</doi><unstructured_citation>W. Zhang, Z. Zhang, D. Qi, and Y.Liu, &quot;Automatic crack detection and classification method for subway tunnel safety monitoring,&quot; Sensors, vol. 14, no. 10, pp. 19307-19328, 2014.</unstructured_citation></citation><citation key="ref13"><doi>10.1007/978-3-319-19024-2_6</doi><unstructured_citation>Y.Kaewaramsri, K. Woraratpanya, ImprovedTriangle Box-The Fractal Dimension Estimation Counting Process, in H. Unger, P. Meesad, S. Boonkrong (Eds.), Springer International Publishing, Recent Developments in Information and Communication Technology, 2015, pp. 53-611</unstructured_citation></citation><citation key="ref14"><doi>10.1109/TIM.2012.2232471</doi><unstructured_citation>A. Bernieri, G. Betta, L. Ferrigno, and M. Laracca, &quot;Crack depth estimation by using a multi-frequency ECT method,&quot; IEEE Trans. Instrum. Meas., vol. 62, no. 3, pp. 544-552, Mar. 2013.</unstructured_citation></citation><citation key="ref15"><journal_title>Optik - Int J Light Electron Opt</journal_title><author>Mahgoub Ahmed Talab</author><volume>127</volume><first_page>1030</first_page><cYear>2016</cYear><doi>10.1016/j.ijleo.2015.09.147</doi><unstructured_citation>Ahmed Mahgoub Ahmed Talab, Zhangcan Huang, Fan Xi, Liu Hai Ming, Detection crack in the image using Otsu method and multiple filtering in image processing techniques, Optik - Int. J. Light Electron Opt. 127 (2016) 1030-1033.</unstructured_citation></citation><citation key="ref16"><doi>10.1109/ICIP.2016.7533052</doi><unstructured_citation>L. Zhang, F. Yang, Y. Daniel Zhang, and Y. J. Zhu, &quot;Road crack detection using deep convolutional neural network,&quot; in Proceedings of the IEEE International Conference on Image Processing(ICIP '16), pp.3708-3712, Phoenix, Ariz, USA, September 2016.</unstructured_citation></citation><citation key="ref17"><doi>10.1109/ICIP.2014.7025160</doi><unstructured_citation>H. Oliveira and P. L. Correia, &quot;Crackit-An image processing toolbox for crack detection and characterization,&quot; Proc. IEEE ICIP, pp. 798-802, 2014.</unstructured_citation></citation><citation key="ref18"><doi>10.1109/ICIP.2014.7025159</doi><unstructured_citation>K. Fernandes and L. Ciobanu, &quot;Pavement pathologies classification using graph-based features,&quot; Proc. IEEE ICIP, pp. 793-797, 2014.</unstructured_citation></citation><citation key="ref19"><doi>10.22260/ISARC2018/0094</doi><unstructured_citation>2018 - Özgenel, Ç.F., Gönenç Sorguç, A. &quot;Performance Comparison of Pretrained Convolutional Neural Networks on Crack Detection in Buildings,&quot; ISARC 2018, Berlin.</unstructured_citation></citation></citation_list>
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