{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:36:54Z","timestamp":1772908614943,"version":"3.50.1"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea (NRF) grant funded by the Korea Government","doi-asserted-by":"publisher","award":["NRF-2020R1F1A1076812"],"award-info":[{"award-number":["NRF-2020R1F1A1076812"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3037719","type":"journal-article","created":{"date-parts":[[2020,11,12]],"date-time":"2020-11-12T21:16:33Z","timestamp":1605215793000},"page":"206289-206302","source":"Crossref","is-referenced-by-count":4,"title":["O-Net: Dangerous Goods Detection in Aviation Security Based on U-Net"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5754-6600","authenticated-orcid":false,"given":"Woong","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7688-3530","authenticated-orcid":false,"given":"Sungchan","family":"Jun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0900-8028","authenticated-orcid":false,"given":"Sumin","family":"Kang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2041-0221","authenticated-orcid":false,"given":"Chulung","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref31","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref30","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref37","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":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref34","first-page":"4278","article-title":"Inception-v4, inception-resnet and the impact of residual connections on learning","author":"szegedy","year":"2017","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-27272-2_9"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/EWDTS.2019.8884452"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/IS.2018.8710471"},{"key":"ref63","first-page":"271","article-title":"Dense multi-path U-Net for ischemic stroke lesion segmentation in multiple image modalities","author":"dolz","year":"2018","journal-title":"International MICCAI Brainlesion Workshop"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2924744"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.31142\/ijtsrd23422"},{"key":"ref65","article-title":"W-Net: Reinforced U-Net for density map estimation","author":"valloli","year":"2019","journal-title":"arXiv 1903 11249"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101557"},{"key":"ref29","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref67","first-page":"1","article-title":"Pre-training on grayscale ImageNet improves medical image classification","author":"xie","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref2","year":"2019","journal-title":"In Numbers World Air Transport Statistics 2019"},{"key":"ref1","year":"2019","journal-title":"WATS World Air Transport Statistics 2019"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/vision3020024"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-89350-9_30"},{"key":"ref21","first-page":"29","article-title":"Aviation security screeners visual abilities & visual knowledge measurement","author":"schwaninger","year":"2005","journal-title":"IEEE Aerosp Electron Syst Mag"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1118\/1.3517194"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.radphyschem.2004.04.111"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2007.09.014"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1117\/12.2512451"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_34"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964798"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.103"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.08.025"},{"key":"ref55","article-title":"Recurrent residual convolutional neural network based on U-Net (R2U-Net) for medical image segmentation","author":"alom","year":"2018","journal-title":"arXiv 1802 06955"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-36711-4_13"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32248-9_28"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ergon.2013.11.003"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssci.2017.06.005"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.690"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1155\/2008\/579416"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CCECE.2004.1345057"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.jairtraman.2016.05.005"},{"key":"ref15","year":"2019","journal-title":"IOSA Standards Manual"},{"key":"ref16","year":"0"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CCST.2015.7389657"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"4330","DOI":"10.3390\/molecules24234330","article-title":"Development of inert, polymer-bonded simulants for explosives detection systems based on transmission X-ray","volume":"24","author":"vah?i?","year":"2019","journal-title":"Molecules"},{"key":"ref19","article-title":"Detecting explosives or other contraband by employing transmitted and scattered X-rays","author":"krug","year":"1997"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1177\/1541931214581477"},{"key":"ref3","year":"2004","journal-title":"The 9\/11 Commission Report The Final Report of the National Commission on Terrorist Attacks Upon the United States"},{"key":"ref6","first-page":"35","article-title":"Islamist fundamentalist and separatist attacks against civil aviation since 11th Sep. 2001","author":"hunter","year":"2011","journal-title":"Aviation security challenges and solutions"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1086\/519816"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CCST.2009.5335572"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CCST.2015.7389652"},{"key":"ref49","article-title":"LadderNet: Multi-path networks based on U-Net for medical image segmentation","author":"zhuang","year":"2018","journal-title":"arXiv 1810 07810"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.proeng.2016.01.010"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"ref45","article-title":"Rethinking atrous convolution for semantic image segmentation","author":"chen","year":"2017","journal-title":"arXiv 1706 05587"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00448"},{"key":"ref47","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref41","article-title":"YOLOv3: An incremental improvement","author":"redmon","year":"2018","journal-title":"arXiv 1804 02767"},{"key":"ref44","article-title":"Semantic image segmentation with deep convolutional nets and fully connected CRFs","author":"chen","year":"2014","journal-title":"arXiv 1412 7062"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09257432.pdf?arnumber=9257432","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T15:57:00Z","timestamp":1642003020000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9257432\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":67,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3037719","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}