{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T17:01:04Z","timestamp":1774630864857,"version":"3.50.1"},"reference-count":53,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,17]]},"DOI":"10.1109\/bigdata55660.2022.10021040","type":"proceedings-article","created":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T14:35:23Z","timestamp":1674743723000},"page":"6378-6386","source":"Crossref","is-referenced-by-count":70,"title":["Crowdsensing-based Road Damage Detection Challenge (CRDDC\u20192022)"],"prefix":"10.1109","author":[{"given":"Deeksha","family":"Arya","sequence":"first","affiliation":[{"name":"The University of Tokyo,Centre for Spatial Information Science,Tokyo,Japan"}]},{"given":"Hiroya","family":"Maeda","sequence":"additional","affiliation":[{"name":"UrbanX Technologies, Inc,Tokyo,Japan"}]},{"given":"Sanjay Kumar","family":"Ghosh","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology,Department of Civil Engineering,Roorkee,India,247667"}]},{"given":"Durga","family":"Toshniwal","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology,Department of Computer Science and Engineering,Roorkee,India,247667"}]},{"given":"Hiroshi","family":"Omata","sequence":"additional","affiliation":[{"name":"The University of Tokyo,Centre for Spatial Information Science,Tokyo,Japan"}]},{"given":"Takehiro","family":"Kashiyama","sequence":"additional","affiliation":[{"name":"Osaka University of Economics,Faculty of Economics,Japan"}]},{"given":"Yoshihide","family":"Sekimoto","sequence":"additional","affiliation":[{"name":"The University of Tokyo,Centre for Spatial Information Science,Tokyo,Japan"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622092"},{"key":"ref12","first-page":"5216","article-title":"Varying adaptive ensemble of deep detectors for road damage detection","author":"manikandan","year":"2018","journal-title":"2018 IEEE International Conference on Big Data (Big Data)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622354"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622599"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00953"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.89"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622327"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622318"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2021.107133"},{"key":"ref16","article-title":"Generative adversarial network for road damage detection","author":"maeda","year":"2020","journal-title":"Computer-Aided Civil and Infrastructure Engineering"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1111\/mice.12387"},{"key":"ref18","article-title":"Rdd2020: an image dataset for smartphone-based road damage detection and classification","volume":"1","author":"arya","year":"2021","journal-title":"Mendeley Data"},{"key":"ref51","article-title":"Attention is all you need","volume":"30","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01170"},{"key":"ref46","article-title":"ultralytics\/yolov5: v6.1 - TensorRT, TensorFlow Edge TPU and OpenVINO Export and Inference","author":"jocher","year":"2022"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00978"},{"key":"ref48","article-title":"YOLOv5","year":"2020"},{"key":"ref47","article-title":"YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","author":"wang","year":"2022","journal-title":"arXiv preprint arXiv 2207 02696"},{"key":"ref42","article-title":"Yolov3: An incremental improvement","author":"redmon","year":"2018","journal-title":"arXiv preprint arXiv 1804 02767"},{"key":"ref41","first-page":"7263","article-title":"Yolo9000: better, faster, stronger","author":"redmon","year":"2017","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref43","article-title":"Yolov4: Optimal speed and accuracy of object detection","author":"bochkovskiy","year":"2020","journal-title":"arXiv preprint arXiv 2004 10934"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622025"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2021.103935"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8621899"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1080\/01441647.2022.2132314"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-16-8837-9_1"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i11.21571"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/IRTM54583.2022.9791529"},{"key":"ref40","first-page":"779","article-title":"You only look once: Unified, real-time object detection","author":"redmon","year":"2016","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref35","article-title":"Transfer learning-based road damage detection for multiple countries","author":"arya","year":"2020","journal-title":"arXiv preprint arXiv 2008 13253"},{"key":"ref34","article-title":"Rdd2022: A multi-national image dataset for automatic road damage detection","author":"arya","year":"2022"},{"key":"ref37","article-title":"Faster r-cnn: Towards real-time object detection with region proposal networks","volume":"28","author":"ren","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref36","first-page":"1440","article-title":"Fast r-cnn","author":"girshick","year":"2015","journal-title":"Proceedings of the IEEE International Conference on Computer Vision"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref30","article-title":"The 1st data science for pavements challenge","author":"behzadian","year":"2022","journal-title":"arXiv preprint arXiv 2206 04874"},{"key":"ref33","article-title":"RDD2022 - The multi-national Road Damage Dataset released through CRDDC&#x2019;2022","author":"arya","year":"2022"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0733-5"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3389\/phrs.2022.1604499"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssci.2021.105513"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00644"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9378047"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377911"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377991"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377847"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377790"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377774"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377833"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377923"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377751"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9377871"}],"event":{"name":"2022 IEEE International Conference on Big Data (Big Data)","location":"Osaka, Japan","start":{"date-parts":[[2022,12,17]]},"end":{"date-parts":[[2022,12,20]]}},"container-title":["2022 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10020192\/10020156\/10021040.pdf?arnumber=10021040","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T17:07:26Z","timestamp":1676912846000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10021040\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,17]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/bigdata55660.2022.10021040","relation":{},"subject":[],"published":{"date-parts":[[2022,12,17]]}}}