{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T14:13:04Z","timestamp":1783865584802,"version":"3.55.0"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Kunshan Municipal Government research funding"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3286548","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T17:27:02Z","timestamp":1686850022000},"page":"60490-60500","source":"Crossref","is-referenced-by-count":17,"title":["Interpretability-Aware Industrial Anomaly Detection Using Autoencoders"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2275-9438","authenticated-orcid":false,"given":"Rui","family":"Jiang","sequence":"first","affiliation":[{"name":"Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yijia","family":"Xue","sequence":"additional","affiliation":[{"name":"Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5618-5791","authenticated-orcid":false,"given":"Dongmian","family":"Zou","sequence":"additional","affiliation":[{"name":"Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-017-1117-8"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07066-y"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3439950"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TSM.2022.3164904"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TCPMT.2012.2207460"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TCPMT.2021.3126083"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2018.2886031"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ICPS51978.2022.9816942"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3069920"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2899901"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00982"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3007337"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/MAES.2010.5546306"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2972628"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI45749.2020.9098686"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2008.4540979"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.procir.2019.02.123"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2021.103627"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01096"},{"key":"ref50","first-page":"7354","article-title":"Self-attention generative adversarial networks","author":"zhang","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00871"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00867"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108102"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICEngTechnol.2017.8308186"},{"key":"ref42","first-page":"1","article-title":"Robust subspace recovery layer for unsupervised anomaly detection","author":"lai","year":"2020","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/2689746.2689747"},{"key":"ref44","first-page":"3538","article-title":"Robust variational autoencoding with Wasserstein penalty for novelty detection","volume":"206","author":"lai","year":"2023","journal-title":"Proc 26th Int Conf Artif Intell Statist"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58520-4_29"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01392"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1016\/j.procs.2015.08.220","article-title":"Survey on anomaly detection using data mining techniques","volume":"60","author":"agrawal","year":"2015","journal-title":"Proc Journal of Computer Science"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-60566-314-2.ch027"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2008.4587510"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/65.283931"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.5120\/13715-1478"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.70731"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2003.814797"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-46145-0_17"},{"key":"ref35","article-title":"Anomaly detection using one-class neural networks","author":"chalapathy","year":"2018","journal-title":"arXiv 1802 06360"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00356"},{"key":"ref37","first-page":"3077","article-title":"Improving one-class SVM for anomaly detection","author":"li","year":"2003","journal-title":"Proc Int Conf Mach Learn Cybern"},{"key":"ref36","first-page":"4393","article-title":"Deep one-class classification","author":"ruff","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065720500604"},{"key":"ref30","first-page":"622","article-title":"Ganomaly: Semi-supervised anomaly detection via adversarial training","author":"akcay","year":"2018","journal-title":"Vision Computer"},{"key":"ref33","first-page":"37","article-title":"Autoencoders, unsupervised learning, and deep architectures","author":"baldi","year":"2012","journal-title":"Proc ICML"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68799-1_51"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2007.03.025"},{"key":"ref1","first-page":"366","article-title":"An application of machine learning to anomaly detection","volume":"377","author":"lane","year":"1997","journal-title":"Proc 20th Nat Inf Syst Secur Conf"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.03.028"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989778"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2017.09.021"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1023\/B:AIRE.0000045502.10941.a9"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2017.2744419"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1002\/stc.2296"},{"key":"ref64","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ISIE45552.2021.9576231"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01400-4"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1145\/3338840.3355641"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"4511","DOI":"10.1109\/TGRS.2013.2282355","article-title":"Ship detection in high-resolution optical imagery based on anomaly detector and local shape feature","volume":"52","author":"shi","year":"2014","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.027"},{"key":"ref28","first-page":"372","article-title":"Improving unsupervised defect segmentation by applying structural similarity to autoencoders","author":"bergmann","year":"2019","journal-title":"Proc 14th Int Joint Conf Comput Vis Imag Comput Graph Theory Appl"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/WTS.2018.8363930"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref62","author":"dabhi","year":"2022","journal-title":"Casting product image data for quality inspection"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10153539.pdf?arnumber=10153539","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T19:34:48Z","timestamp":1689017688000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10153539\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":67,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3286548","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}