{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T20:30:58Z","timestamp":1770150658118,"version":"3.49.0"},"reference-count":39,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,18]],"date-time":"2023-06-18T00:00:00Z","timestamp":1687046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100014103","name":"Key R&D Program of Shandong Province","doi-asserted-by":"publisher","award":["2022CXGC020106"],"award-info":[{"award-number":["2022CXGC020106"]}],"id":[{"id":"10.13039\/100014103","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,18]]},"DOI":"10.1109\/ijcnn54540.2023.10191285","type":"proceedings-article","created":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T17:30:03Z","timestamp":1690997403000},"page":"1-8","source":"Crossref","is-referenced-by-count":2,"title":["DCP-Net: The Defect Detection Method of Industrial Product based on Dual Collaborative Paths"],"prefix":"10.1109","author":[{"given":"Zekai","family":"Zhang","sequence":"first","affiliation":[{"name":"Qilu University of Technology,Shandong Computer Science Center,Jinan,China"}]},{"given":"Mingle","family":"Zhou","sequence":"additional","affiliation":[{"name":"Qilu University of Technology,Shandong Computer Science Center,Jinan,China"}]},{"given":"Honglin","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Science, Shandong Normal University,Jinan,China"}]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"Qilu University of Technology,Shandong Computer Science Center,Jinan,China"}]},{"given":"Gang","family":"Li","sequence":"additional","affiliation":[{"name":"Qilu University of Technology,Shandong Computer Science Center,Jinan,China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN55064.2022.9892172"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2018.12.043"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00203"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01167"},{"key":"ref36","first-page":"740","article-title":"Microsoft coco: Common objects in context","author":"lin","year":"2014","journal-title":"European Conference on Computer Vision"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CCHI.2019.8901952"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8803154"},{"key":"ref11","article-title":"Mask R -CNN","author":"he","year":"2018","journal-title":"ArXiv"},{"key":"ref33","article-title":"YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications","author":"li","year":"2022","journal-title":"ArXiv"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref32","article-title":"PP-YOLOE: An evolved version of YOLO","author":"xu","year":"2022","journal-title":"ArXiv"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref39","article-title":"Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression","author":"zheng","year":"2019","journal-title":"ArXiv"},{"key":"ref16","article-title":"EfficientNet: Rethinking Model Scaling for Con-volutional Neural Networks","volume":"97","author":"tan","year":"2019","journal-title":"International Conference on Machine Learning"},{"key":"ref38","article-title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","author":"simonyan","year":"2015","journal-title":"ArXiv"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00913"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref24","article-title":"BAM: Bottleneck Attention Module","author":"park","year":"2018","journal-title":"ArXiv"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref26","article-title":"Attention Is All You Need","volume":"30","author":"vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems 30 (NIPS 2017)"},{"key":"ref25","article-title":"Global Attention Mecha-nism: Retain Information to Enhance Channel-Spatial Interactions","author":"liu","year":"2021","journal-title":"ArXiv"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"ref22","article-title":"Implicit Feature Pyramid Network for Object Detection","author":"wang","year":"2020","journal-title":"ArXiv"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00720"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"ref27","article-title":"NAM: Normalization-based Attention Module","author":"liu","year":"2021","journal-title":"ArXiv"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref4","article-title":"YOLOv4: Optimal Speed and Accuracy of Object Detection","author":"bochkovskiy","year":"2020","journal-title":"ArXiv"},{"key":"ref3","article-title":"YOLOv3: An Incremental Improvement","author":"redmon","year":"2018","journal-title":"ArXiv"},{"key":"ref6","article-title":"YOLOX: Exceeding YOLO Series in 2021","author":"ge","year":"2021","journal-title":"ArXiv"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01284"}],"event":{"name":"2023 International Joint Conference on Neural Networks (IJCNN)","location":"Gold Coast, Australia","start":{"date-parts":[[2023,6,18]]},"end":{"date-parts":[[2023,6,23]]}},"container-title":["2023 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10190990\/10190992\/10191285.pdf?arnumber=10191285","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T17:45:08Z","timestamp":1692639908000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10191285\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,18]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/ijcnn54540.2023.10191285","relation":{},"subject":[],"published":{"date-parts":[[2023,6,18]]}}}