{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:12:34Z","timestamp":1760710354221,"version":"3.41.2"},"reference-count":31,"publisher":"American Society of Civil Engineers (ASCE)","issue":"6","content-domain":{"domain":["ascelibrary.org"],"crossmark-restriction":true},"short-container-title":["J. Comput. Civ. Eng."],"published-print":{"date-parts":[[2020,11]]},"DOI":"10.1061\/(asce)cp.1943-5487.0000930","type":"journal-article","created":{"date-parts":[[2020,8,31]],"date-time":"2020-08-31T05:50:33Z","timestamp":1598853033000},"update-policy":"https:\/\/doi.org\/10.1061\/do.news.20190416.0001","source":"Crossref","is-referenced-by-count":25,"title":["Determining Ground Elevations Covered by Vegetation on Construction Sites Using Drone-Based Orthoimage and Convolutional Neural Network"],"prefix":"10.1061","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9661-1022","authenticated-orcid":true,"given":"Yuhan","family":"Jiang","sequence":"first","affiliation":[{"name":"Ph.D. Candidate, Dept. of Civil, Construction and Environmental Engineering, Marquette Univ., P.O. Box 1881, Milwaukee, WI 53201-1881 (corresponding author). ORCID: ."}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2814-0422","authenticated-orcid":true,"given":"Yong","family":"Bai","sequence":"additional","affiliation":[{"name":"McShane Chair and Professor, Dept. of Civil, Construction and Environmental Engineering, Marquette Univ., P.O. Box 1881, Milwaukee, WI 53201-1881. ORCID: ."}]},{"given":"Sisi","family":"Han","sequence":"additional","affiliation":[{"name":"Graduate Student, Dept. of Civil, Construction and Environmental Engineering, Marquette Univ., P.O. Box 1881, Milwaukee, WI 53201-1881."}]}],"member":"30","reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/drones3030061"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/geosciences8070244"},{"key":"e_1_3_3_5_1","unstructured":"Chollet F. 2015. \u201cKeras: The python deep learning library.\u201d Accessed August 7 2019. https:\/\/keras.io\/."},{"key":"e_1_3_3_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2016.05.019"},{"key":"e_1_3_3_7_1","doi-asserted-by":"crossref","unstructured":"Deng J. W. Dong R. Socher L. Li K. Li and F. Li. 2009. \u201cImageNet: A large-scale hierarchical image database.\u201d In Proc. 2009 IEEE Conf. on Computer Vision and Pattern Recognition 248\u2013255. New York: IEEE.","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_3_8_1","unstructured":"Dettmers T. 2015. \u201cDeep learning in a nutshell: Core concepts.\u201d Accessed August 7 2019. https:\/\/devblogs.nvidia.com\/deep-learning-nutshell-core-concepts\/."},{"key":"e_1_3_3_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2006.11.002"},{"key":"e_1_3_3_10_1","doi-asserted-by":"crossref","unstructured":"Engelcke M. D. Rao D. Z. Wang T. Chi Hay and I. Posner. 2017. \u201cVote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks.\u201d In Proc. 2017 IEEE Int. Conf. on Robotics and Automation (ICRA) 1355\u20131361. New York: IEEE.","DOI":"10.1109\/ICRA.2017.7989161"},{"key":"e_1_3_3_11_1","unstructured":"Geirhos R. P. Rubisch C. Michaelis M. Bethge F. A. Wichmann and W. Brendel. 2019. \u201cImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness.\u201d In Proc. 7th Int. Conf. on Learning Representations (ICLR 2019). Cambridge MA: International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=Bygh9j09KX."},{"key":"e_1_3_3_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2374218"},{"key":"e_1_3_3_13_1","doi-asserted-by":"crossref","unstructured":"Jiang Y. and Y. Bai. 2020a. \u201cDetermination of construction site elevations using drone technology.\u201d In Proc. Construction Research Congress 2020. Reston VA: ASCE.","DOI":"10.1061\/9780784482865.032"},{"key":"e_1_3_3_14_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)CO.1943-7862.0001869"},{"key":"e_1_3_3_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2736553"},{"key":"e_1_3_3_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0926-5805(02)00034-1"},{"key":"e_1_3_3_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2681128"},{"key":"e_1_3_3_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.proeng.2017.07.168"},{"key":"e_1_3_3_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2018.03.006"},{"key":"e_1_3_3_20_1","doi-asserted-by":"publisher","DOI":"10.1080\/15481603.2018.1426091"},{"key":"e_1_3_3_21_1","doi-asserted-by":"crossref","unstructured":"Maggiori E. Y. Tarabalka G. Charpiat and P. Alliez. 2016. \u201cFully convolutional neural networks for remote sensing image classification.\u201d In Proc. 2016 IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS) 5071\u20135074. New York: IEEE.","DOI":"10.1109\/IGARSS.2016.7730322"},{"key":"e_1_3_3_23_1","unstructured":"Nair V. and G. Hinton. 2010. \u201cRectified linear units improve restricted boltzmann machines.\u201d In Proc. 27th Int. Conf. on Machine Learning (ICML 2010) 807\u2013814. Haifa Israel: International Machine Learning Society."},{"key":"e_1_3_3_24_1","doi-asserted-by":"publisher","DOI":"10.6106\/JCEPM.2012.2.3.001"},{"key":"e_1_3_3_25_1","doi-asserted-by":"crossref","unstructured":"Noh H. S. Hong and B. Han. 2015. \u201cLearning deconvolution network for semantic segmentation.\u201d In Proc. 2015 IEEE Int. Conf. on Computer Vision (ICCV 2015) 1520\u20131528. New York: IEEE.","DOI":"10.1109\/ICCV.2015.178"},{"key":"e_1_3_3_26_1","doi-asserted-by":"crossref","unstructured":"Ronneberger O. P. Fischer and T. Brox. 2015. \u201cU-Net: Convolutional networks for biomedical image segmentation.\u201d In Proc. Medical Image Computing and Computer-Assisted Intervention (MICCAI 2015) 234\u2013241. Cham Switzerland: Springer.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_3_28_1","doi-asserted-by":"crossref","unstructured":"Schneider S. G. W. Taylor and S. Kremer. 2018. \u201cDeep learning object detection methods for ecological camera trap data.\u201d In Proc. 2018 15th Conf. on Computer and Robot Vision (CRV) 321\u2013328. New York: IEEE.","DOI":"10.1109\/CRV.2018.00052"},{"key":"e_1_3_3_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"e_1_3_3_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2014.01.004"},{"key":"e_1_3_3_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2015.12.022"},{"key":"e_1_3_3_32_1","doi-asserted-by":"crossref","unstructured":"Theodorus A. M. Nauta and C. Seifert. 2020. \u201cEvaluating CNN interpretability on sketch classification.\u201d In Proc. 12th Int. Conf. on Machine Vision (ICMV 2019). Bellingham WA: Society of Photo-Optical Instrumentation Engineers. https:\/\/doi.org\/10.1117\/12.2559536.","DOI":"10.1117\/12.2559536"},{"key":"e_1_3_3_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.geomorph.2012.08.021"},{"key":"e_1_3_3_34_1","doi-asserted-by":"crossref","unstructured":"Zhao H. J. Shi X. Qi X. Wang and J. Jia. 2017. \u201cPyramid scene parsing network.\u201d In Proc. 2017 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 6230\u20136239. New York: IEEE.","DOI":"10.1109\/CVPR.2017.660"}],"container-title":["Journal of Computing in Civil Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/ascelibrary.org\/doi\/pdf\/10.1061\/%28ASCE%29CP.1943-5487.0000930","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T22:42:20Z","timestamp":1654814540000},"score":1,"resource":{"primary":{"URL":"https:\/\/ascelibrary.org\/doi\/10.1061\/%28ASCE%29CP.1943-5487.0000930"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11]]},"references-count":31,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020,11]]}},"alternative-id":["10.1061\/(ASCE)CP.1943-5487.0000930"],"URL":"https:\/\/doi.org\/10.1061\/(asce)cp.1943-5487.0000930","relation":{},"ISSN":["0887-3801","1943-5487"],"issn-type":[{"type":"print","value":"0887-3801"},{"type":"electronic","value":"1943-5487"}],"subject":[],"published":{"date-parts":[[2020,11]]},"assertion":[{"value":"2020-02-17","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-06-15","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2020-08-31","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"04020049"}}