{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T11:22:39Z","timestamp":1762341759871,"version":"3.37.3"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Canscan Inc., Montreal, QC, Canada"},{"DOI":"10.13039\/501100004489","name":"Mitacs","doi-asserted-by":"publisher","award":["IT12857"],"award-info":[{"award-number":["IT12857"]}],"id":[{"id":"10.13039\/501100004489","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Instrum. Meas."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tim.2021.3117629","type":"journal-article","created":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T03:26:14Z","timestamp":1633404374000},"page":"1-13","source":"Crossref","is-referenced-by-count":7,"title":["An HRCR-CNN Framework for Automated Security Seal Detection on the Shipping Container"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0876-2689","authenticated-orcid":false,"given":"Zhila","family":"Bahrami","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3461-0045","authenticated-orcid":false,"given":"Ran","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1512-4335","authenticated-orcid":false,"given":"Rakiba","family":"Rayhana","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7241-3483","authenticated-orcid":false,"given":"Zheng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"ref32","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1016\/j.dt.2020.10.006"},{"key":"ref30","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017","journal-title":"arXiv 1704 04861"},{"doi-asserted-by":"publisher","key":"ref36","DOI":"10.1109\/TIM.2020.3016108"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1063\/5.0000980"},{"doi-asserted-by":"publisher","key":"ref34","DOI":"10.1109\/ICCV.2019.00982"},{"key":"ref10","article-title":"YOLOv3: An incremental improvement","author":"redmon","year":"2018","journal-title":"arXiv 1804 02767"},{"year":"2021","author":"jocher","journal-title":"Ultralytics\/YOLOv5 V4 0–nn SiLU() Activations Weights & Biases Logging PyTorch Hub Integration","key":"ref11"},{"key":"ref12","first-page":"1","article-title":"YOLOv4-5D: An effective and efficient object detector for autonomous driving","volume":"70","author":"cai","year":"2021","journal-title":"IEEE Trans Instrum Meas"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1007\/978-3-319-46448-0_2"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1109\/TIM.2021.3118092"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref16","first-page":"1","article-title":"RetinaNet with difference channel attention and adaptively spatial feature fusion for steel surface defect detection","volume":"70","author":"cheng","year":"2021","journal-title":"IEEE Trans Instrum Meas"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/CVPR.2016.91"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1109\/CVPR.2018.00377"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1109\/ICME.2018.8486561"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1109\/CVPR.2017.351"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/ICCV.2015.169"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1016\/j.imavis.2020.103910"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/TPAMI.2015.2389824"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/CVPR.2016.90"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/CVPR42600.2020.01309"},{"key":"ref5","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","author":"ren","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref8","first-page":"379","article-title":"R-FCN: Object detection via region-based fully convolutional networks","author":"dai","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1109\/TIM.2019.2958580"},{"key":"ref2","article-title":"HRDNet: High-resolution detection network for small objects","author":"liu","year":"2020","journal-title":"arXiv 2006 07607"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1007\/s11263-019-01247-4"},{"year":"2016","author":"hofman","article-title":"System and method for detecting cargo container seals","key":"ref1"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.5121\/csit.2019.91713"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1007\/978-3-030-01228-1_20"},{"key":"ref21","article-title":"SNIPER: Efficient multi-scale training","author":"singh","year":"2018","journal-title":"arXiv 1805 09300"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1109\/TMM.2016.2642789"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/ICCV.2015.135"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.1109\/CVPR.2017.211"},{"key":"ref25","first-page":"1","article-title":"Gated contextual features for salient object detection","volume":"70","author":"gupta","year":"2021","journal-title":"IEEE Trans Instrum Meas"}],"container-title":["IEEE Transactions on Instrumentation and Measurement"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/19\/9259274\/09558820.pdf?arnumber=9558820","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:51:29Z","timestamp":1652194289000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9558820\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/tim.2021.3117629","relation":{},"ISSN":["0018-9456","1557-9662"],"issn-type":[{"type":"print","value":"0018-9456"},{"type":"electronic","value":"1557-9662"}],"subject":[],"published":{"date-parts":[[2021]]}}}