{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,24]],"date-time":"2025-08-24T01:14:18Z","timestamp":1755998058028,"version":"3.37.3"},"reference-count":27,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T00:00:00Z","timestamp":1656547200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Funding of Post-Doctor","award":["E00120210001","ZR2020MF132","0104060540508"],"award-info":[{"award-number":["E00120210001","ZR2020MF132","0104060540508"]}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["E00120210001","ZR2020MF132","0104060540508"],"award-info":[{"award-number":["E00120210001","ZR2020MF132","0104060540508"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004295","name":"Shandong University of Science and Technology","doi-asserted-by":"publisher","award":["E00120210001","ZR2020MF132","0104060540508"],"award-info":[{"award-number":["E00120210001","ZR2020MF132","0104060540508"]}],"id":[{"id":"10.13039\/501100004295","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2022,6,30]]},"abstract":"<jats:p>In this paper, a modified YOLOv3 net has been proposed for surface defect detection. Different from other pixel-level segmenting methods, YOLOv3 locates the regions of surface defects with bounding rectangles. Compared with conventional detectors, the operating efficiency of YOLOv3 is rather high without generating region proposals by sliding boxes. Although pixel-level details of defects are omitted in the process, the primary information of the location of detects and class labels are extracted by YOLOv3 with high accuracy. This information is sufficient for surface defect inspection, and computational efficiency has been improved, simultaneously. To further light the structure of YOLOv3, loss function optimization and pruning strategy have been adopted in the original YOLOv3. The pruning ratio is determined by the tradeoff between detecting accuracy and computational efficiency. In our experiments, we compared the performance of modified YOLOv3 with several state-of-the-art methods, and modified YOLOv3 achieves the best performance on six types of surface defects in DAGM 2007 dataset.<\/jats:p>","DOI":"10.1155\/2022\/8668149","type":"journal-article","created":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T18:35:24Z","timestamp":1656614124000},"page":"1-10","source":"Crossref","is-referenced-by-count":10,"title":["Surface Defect Detection with Modified Real-Time Detector YOLOv3"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8140-1882","authenticated-orcid":true,"given":"Zhihui","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266510, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2515-7413","authenticated-orcid":true,"given":"Houying","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Faculty of Science and Engineering, Macquarie University, NSW 2109, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7309-2936","authenticated-orcid":true,"given":"Xianqing","family":"Jia","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266510, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1010-7229","authenticated-orcid":true,"given":"Yongtang","family":"Bao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266510, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2466-5990","authenticated-orcid":true,"given":"Changmiao","family":"Wang","sequence":"additional","affiliation":[{"name":"Shenzhen Research Institute of Big Data, Shenzhen 518172, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"2","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.compeleceng.2017.12.009","article-title":"Deep learning in big data analytics: a comparative study","volume":"75","author":"B. Jan","year":"2019","journal-title":"Computers & Electrical Engineering"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2319-3"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.5565\/rev\/elcvia.268"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.3390\/s20051459"},{"key":"6","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"A. Krizhevsky","year":"2012","journal-title":"advances in neural information processing systems"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68345-4_37"},{"first-page":"3431","article-title":"Fully convolutional networks for semantic segmentation","author":"J. Long","key":"8"},{"author":"Cognex Vidi of Cognex","key":"9"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2975030"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2894420"},{"first-page":"17","article-title":"Regionlets for generic object detection","author":"X. Wang","key":"12"},{"issue":"1","key":"13","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1109\/TPAMI.2015.2437384","article-title":"Region-based convolutional networks for accurate object detection and segmentation","volume":"38","author":"R. Girshick","year":"2016","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"first-page":"1440","article-title":"Fast r-cnn","author":"R. Girshick","key":"14"},{"key":"15","first-page":"91","article-title":"Faster r-cnn: towards real-time object detection with region proposal networks","volume":"28","author":"S. Ren","year":"2015","journal-title":"advances in neural information processing systems"},{"first-page":"248","article-title":"Imagenet: a large-scale hierarchical image database","author":"J. Deng","key":"16"},{"first-page":"779","article-title":"You only look once: unified, real-time object detection","author":"J. Redmon","key":"17"},{"first-page":"7263","article-title":"YOLO 9000: better, faster, stronger","author":"J. Redmon","key":"18"},{"article-title":"Yolov3: an incremental improvement","year":"2018","author":"J. Redmon","key":"19"},{"article-title":"Yolox: exceeding yolo series in 2021","year":"2021","author":"Z. Ge","key":"20"},{"first-page":"658","article-title":"Generalized intersection over union: a metric and a loss for bounding box regression","author":"H. Rezatofighi","key":"21"},{"first-page":"5406","article-title":"Deep learning with low precision by half-wave Gaussian quantization","author":"Z. Cai","key":"22"},{"article-title":"Pruning filters for efficient convnet","year":"2016","author":"H. Li","key":"23"},{"author":"Z. Liu","key":"24","article-title":"Learning efficient convolutional networks through network slimming"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2765695"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.3390\/s20061562"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"}],"container-title":["Journal of Sensors"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2022\/8668149.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2022\/8668149.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/js\/2022\/8668149.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T18:35:35Z","timestamp":1656614135000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/js\/2022\/8668149\/"}},"subtitle":[],"editor":[{"given":"Sangsoon","family":"Lim","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2022,6,30]]},"references-count":27,"alternative-id":["8668149","8668149"],"URL":"https:\/\/doi.org\/10.1155\/2022\/8668149","relation":{},"ISSN":["1687-7268","1687-725X"],"issn-type":[{"type":"electronic","value":"1687-7268"},{"type":"print","value":"1687-725X"}],"subject":[],"published":{"date-parts":[[2022,6,30]]}}}