{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T09:15:02Z","timestamp":1781946902018,"version":"3.54.5"},"reference-count":54,"publisher":"American Society of Civil Engineers (ASCE)","issue":"1","content-domain":{"domain":["ascelibrary.org"],"crossmark-restriction":true},"short-container-title":["J. Comput. Civ. Eng."],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1061\/jccee5.cpeng-6549","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T12:57:38Z","timestamp":1758286658000},"update-policy":"https:\/\/doi.org\/10.1061\/do.news.20190416.0001","source":"Crossref","is-referenced-by-count":2,"title":["Automated Detection and Quantification of Sewer Pipe Cracks Using a CNN-Based Approach"],"prefix":"10.1061","volume":"40","author":[{"given":"Chenhao","family":"Yang","sequence":"first","affiliation":[{"name":"Zhejiang Univ.","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David Z.","family":"Zhu","sequence":"additional","affiliation":[{"name":"Univ. of Alberta","place":["Canada"]},{"name":"Ningbo Univ.","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tuqiao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Zhejiang Univ.","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Wan","sequence":"additional","affiliation":[{"name":"Tsinghua Univ.","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3874-0306","authenticated-orcid":true,"given":"Yiyi","family":"Ma","sequence":"additional","affiliation":[{"name":"Zhejiang Univ.","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"30","reference":[{"key":"e_1_3_5_2_1","doi-asserted-by":"crossref","unstructured":"Bertalm\u00edo M. A. L. Bertozzi and G. Sapiro. 2001. \u201cNavier-stokes fluid dynamics and image and video inpainting.\u201d In Vol. 1 of Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition 355\u2013362. New York: IEEE.","DOI":"10.1109\/CVPR.2001.990497"},{"key":"e_1_3_5_3_1","first-page":"5014814","article-title":"Aircraft pipe gap inspection on raw point cloud from a single view","volume":"71","author":"Cao T.","year":"2022","unstructured":"Cao, T., L. Zhou, L. Qu, Y. Liu, C. Ding, and Q. Wu. 2022. \u201cAircraft pipe gap inspection on raw point cloud from a single view.\u201d IEEE Trans. Instrum. Meas. 71 (Jun): 5014814. https:\/\/doi.org\/10.1109\/TIM.2022.3186058.","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"e_1_3_5_4_1","doi-asserted-by":"crossref","unstructured":"Chen L. C. Y. Zhu G. Papandreou F. Schroff and H. Adam. 2018. \u201cEncoder-decoder with atrous separable convolution for semantic image segmentation.\u201d In Vol. 11211 of Proc. European Conf. on Computer Vision (ECCV) 833\u2013851. Berlin: Springer. https:\/\/doi.org\/10.1007\/978-3-030-01234-2_49.","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"e_1_3_5_5_1","unstructured":"China Association for Engineering Construction Standardization. 2021. Technical specification for inspection and evaluation of outdoor sewer. T\/CECS 1507-2023. Beijing: China Planning Press."},{"key":"e_1_3_5_6_1","doi-asserted-by":"crossref","unstructured":"Chollet F. 2017. \u201cXception: Deep learning with depthwise separable convolutions.\u201d In Proc. 30th IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 1800\u20131807. New York: IEEE. https:\/\/doi.org\/10.1109\/CVPR.2017.195.","DOI":"10.1109\/CVPR.2017.195"},{"key":"e_1_3_5_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs12060968"},{"key":"e_1_3_5_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2021.107630"},{"key":"e_1_3_5_9_1","unstructured":"Diederik P. K. and B. Jimmy. 2014. \u201cAdam: A method for stochastic optimization.\u201d Preprint submitted December 22 2014. https:\/\/arxiv.org\/abs\/1412.6980."},{"key":"e_1_3_5_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/361237.361242"},{"key":"e_1_3_5_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2022.104399"},{"key":"e_1_3_5_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2019.102849"},{"key":"e_1_3_5_13_1","doi-asserted-by":"crossref","unstructured":"Haurum J. B. and T. B. Moeslund. 2021. \u201cSewer-ML: A multi-label sewer defect classification dataset and benchmark.\u201d In Proc. IEEE\/CVF Conf. on Computer Vision and Pattern Recognition (CVPR) 13451\u201313462. New York: IEEE. https:\/\/doi.org\/10.1109\/CVPR46437.2021.01325.","DOI":"10.1109\/CVPR46437.2021.01325"},{"key":"e_1_3_5_14_1","doi-asserted-by":"crossref","unstructured":"He K. X. Zhang S. Ren and J. Sun. 2016. \u201cDeep residual learning for image recognition.\u201d In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 770\u2013778. New York: IEEE. https:\/\/doi.org\/10.1109\/CVPR.2016.90.","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_5_15_1","doi-asserted-by":"publisher","DOI":"10.1061\/JPSEA2.PSENG-1454"},{"key":"e_1_3_5_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2015.01.008"},{"key":"e_1_3_5_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2018.03.028"},{"key":"e_1_3_5_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2867951"},{"key":"e_1_3_5_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tust.2023.105430"},{"key":"e_1_3_5_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2022.110727"},{"key":"e_1_3_5_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2022.104595"},{"key":"e_1_3_5_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2019.04.013"},{"key":"e_1_3_5_23_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)PS.1949-1204.0000629"},{"key":"e_1_3_5_24_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)IS.1943-555X.0000553"},{"key":"e_1_3_5_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2018.08.005"},{"key":"e_1_3_5_26_1","unstructured":"National Development and Reform Commission of the People\u2019s Republic of China. 2012. Technical specification for inspection and evaluation of urban drainage. CJJ 181\u20132012. Beijing: China Architecture & Building Press."},{"key":"e_1_3_5_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3168660"},{"key":"e_1_3_5_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2020.103383"},{"key":"e_1_3_5_29_1","doi-asserted-by":"crossref","unstructured":"Qi J. M. Smith and N. Barclay. 2022. \u201cEmpirical data-based condition prediction for stormwater pipelines with machine learning.\u201d In Proc. SoutheastCon 2022 316\u2013322. New York: IEEE. https:\/\/doi.org\/10.1109\/SoutheastCon48659.2022.9764033.","DOI":"10.1109\/SoutheastCon48659.2022.9764033"},{"key":"e_1_3_5_30_1","doi-asserted-by":"crossref","unstructured":"Qin X. Z. Wang Y. Bai X. Xie and H. Jia. 2020. \u201cFFA-Net: Feature fusion attention network for single image dehazing.\u201d In Vol. 34 of Proc. 34th AAAI Conf. on Artificial Intelligence the 32nd Innovative Applications of Artificial Intelligence Conf. and the 10th AAAI Symp. on Educational Advances in Artificial Intelligence 11908\u201311915. Washington DC: Association for the Advancement of Artificial Intelligence.","DOI":"10.1609\/aaai.v34i07.6865"},{"key":"e_1_3_5_31_1","doi-asserted-by":"crossref","unstructured":"Ran Q. N. Wang X. Wang Z. He and Y. Zhao. 2024. \u201cImproved U-net drainage pipe defects detection algorithm based on CBMA attention mechanism.\u201d In Proc. 9th Int. Conf. on Electronic Technology and Information Science (ICETIS) 342\u2013347. New York: IEEE. https:\/\/doi.org\/10.1109\/ICETIS61828.2024.10593723.","DOI":"10.1109\/ICETIS61828.2024.10593723"},{"key":"e_1_3_5_32_1","doi-asserted-by":"publisher","DOI":"10.2166\/wst.2022.263"},{"key":"e_1_3_5_33_1","doi-asserted-by":"crossref","unstructured":"Sandler M. A. Howard M. Zhu A. Zhmoginov and L. Chen. 2018. \u201cMobileNetV2: Inverted residuals and linear bottlenecks.\u201d In Proc. IEEE\/CVF Conf. on Computer Vision and Pattern Recognition (CVPR) 4510\u20134520. New York: IEEE. https:\/\/doi.org\/10.1109\/CVPR.2018.00474.","DOI":"10.1109\/CVPR.2018.00474"},{"key":"e_1_3_5_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2646371"},{"key":"e_1_3_5_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2023.163562"},{"key":"e_1_3_5_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2021.103912"},{"key":"e_1_3_5_37_1","doi-asserted-by":"publisher","DOI":"10.1111\/mice.12840"},{"key":"e_1_3_5_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2010.2050290"},{"issue":"6","key":"e_1_3_5_39_1","first-page":"130","article-title":"Evaluation method of municipal sewer health status based on YOLOv5","volume":"58","author":"Wang H.","year":"2022","unstructured":"Wang, H., H. Xie, Y. Gao, J. Liu, X. Song, W. Luo, Z. Zhang, and D. Yan. 2022. \u201cEvaluation method of municipal sewer health status based on YOLOv5.\u201d [In Chinese.] Water Wastewater Eng. 58 (6): 130\u2013136. https:\/\/doi.org\/10.13789\/j.cnki.wwe1964.2022.03.12.0004.","journal-title":"Water Wastewater Eng."},{"key":"e_1_3_5_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2020.103438"},{"key":"e_1_3_5_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tust.2021.103840"},{"key":"e_1_3_5_42_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)IS.1943-555X.0000729"},{"key":"e_1_3_5_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tust.2023.105480"},{"key":"e_1_3_5_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2023.162465"},{"key":"e_1_3_5_45_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-013-0355-5"},{"key":"e_1_3_5_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2019.2900170"},{"key":"e_1_3_5_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.08.013"},{"key":"e_1_3_5_48_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.07.103"},{"key":"e_1_3_5_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2022.104300"},{"key":"e_1_3_5_50_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2019.102967"},{"key":"e_1_3_5_51_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2021.103622"},{"key":"e_1_3_5_52_1","doi-asserted-by":"publisher","DOI":"10.1088\/1538-3873\/ac6e07"},{"issue":"1","key":"e_1_3_5_53_1","first-page":"818","article-title":"The current situation and consideration for intelligent detection technology of underground drainage pipeline defects","volume":"49","author":"Zhang J.","year":"2023","unstructured":"Zhang, J., Q. Sun, and L. Li. 2023. \u201cThe current situation and consideration for intelligent detection technology of underground drainage pipeline defects.\u201d [In Chinese.] Supplement, Water Wastewater Eng. 49 (S1): 818\u2013822. https:\/\/doi.org\/10.13789\/j.cnki.wwe1964.2023.03.21.0004.","journal-title":"Water Wastewater Eng."},{"issue":"11","key":"e_1_3_5_54_1","first-page":"12","article-title":"An improved DeepLab v3+ image semantic segmentation algorithm incorporating multi-scale features","volume":"29","author":"Zhang W.","year":"2022","unstructured":"Zhang, W., J. Qu, W. Wang, J. Hu, and Q. Wang. 2022. \u201cAn improved DeepLab v3+ image semantic segmentation algorithm incorporating multi-scale features.\u201d Electron. Opt. Control 29 (11): 12\u201316. https:\/\/doi.org\/10.3969\/j.issn.1671-637X.2022.11.003.","journal-title":"Electron. Opt. Control"},{"key":"e_1_3_5_55_1","unstructured":"Zhang Z. 2021. \u201cStudy on mechanical properties of buried cracked concrete drainage pipelines under multi-factor coupling.\u201d [In Chinese.] Master\u2019s thesis School of Water Conservancy and Transportation Zhengzhou Univ."}],"container-title":["Journal of Computing in Civil Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/ascelibrary.org\/doi\/pdf\/10.1061\/JCCEE5.CPENG-6549","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T12:57:44Z","timestamp":1758286664000},"score":1,"resource":{"primary":{"URL":"https:\/\/ascelibrary.org\/doi\/10.1061\/JCCEE5.CPENG-6549"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":54,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["10.1061\/JCCEE5.CPENG-6549"],"URL":"https:\/\/doi.org\/10.1061\/jccee5.cpeng-6549","relation":{},"ISSN":["0887-3801","1943-5487"],"issn-type":[{"value":"0887-3801","type":"print"},{"value":"1943-5487","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"2024-10-16","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-06","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"05025007"}}