{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T18:57:59Z","timestamp":1778871479017,"version":"3.51.4"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2899109","type":"journal-article","created":{"date-parts":[[2019,2,13]],"date-time":"2019-02-13T20:15:43Z","timestamp":1550088943000},"page":"23177-23186","source":"Crossref","is-referenced-by-count":9,"title":["Selective Distillation of Weakly Annotated GTD for Vision-Based Slab Identification System"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9312-6299","authenticated-orcid":false,"given":"Sang Jun","family":"Lee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6023-1837","authenticated-orcid":false,"given":"Sang Woo","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wookyong","family":"Kwon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gyogwon","family":"Koo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2802-9978","authenticated-orcid":false,"given":"Jong Pil","family":"Yun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.04.027"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2818020"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.309"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.754"},{"key":"ref31","author":"hinton","year":"2015","journal-title":"Distilling the knowledge in a neural network"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.06.017"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.12.058"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"key":"ref35","first-page":"742","article-title":"Learning efficient object detection models with knowledge distillation","author":"chen","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref34","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"tarvainen","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.01.124"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.01.026"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2013.2262045"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2864629"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2683641"},{"key":"ref22","first-page":"740","article-title":"Microsoft COCO: Common objects in context","author":"lin","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-007-0090-8"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.344"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.477"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298668"},{"key":"ref25","first-page":"549","article-title":"What&#x2019;s the point: Semantic segmentation with point supervision","author":"bearman","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0823-z"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.10.016"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref58","author":"kingma","year":"2014","journal-title":"Adam A method for stochastic optimization"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref56","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":"ref55","author":"simonyan","year":"0","journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2572683"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.2355\/isijinternational.ISIJINT-2017-695"},{"key":"ref52","first-page":"22","article-title":"Deep textspotter: An end-to-end trainable scene text localization and recognition framework","author":"bu\u0161ta","year":"2017","journal-title":"Proc IEEE Int Conf Comput Vis (ICCV)"},{"key":"ref10","first-page":"2553","article-title":"Deep neural networks for object detection","author":"szegedy","year":"2013","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2656474"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref13","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref14","author":"ioffe","year":"2015","journal-title":"Batch Normalization Accelerating Deep Network Training by Reducing Internal Covariate Shift"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.532"},{"key":"ref16","article-title":"Efficient deep CNN-based fire detection and localization in video surveillance applications","author":"muhammad","year":"0","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2764844"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2804930"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.07.020"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2868976"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2010.2045375"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.09.033"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.01.017"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.01.036"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.10.064"},{"key":"ref49","first-page":"3304","article-title":"End-to-end text recognition with convolutional neural networks","author":"wang","year":"2012","journal-title":"Proc 21st Int Conf Pattern Recognit"},{"key":"ref9","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":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7532963"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.451"},{"key":"ref48","first-page":"3501","article-title":"Reading scene text in deep convolutional sequences","author":"he","year":"2016","journal-title":"Proc 30th AAAI Conf Artif Intell"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2646371"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2017.140"},{"key":"ref41","first-page":"56","article-title":"Detecting text in natural image with connectionist text proposal network","author":"tian","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472154"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.371"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08641386.pdf?arnumber=8641386","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T07:17:36Z","timestamp":1643267856000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8641386\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":59,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2899109","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}