{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T14:07:23Z","timestamp":1784210843782,"version":"3.55.0"},"reference-count":39,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51905160"],"award-info":[{"award-number":["51905160"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Fund for Excellent Young Scholars of Hunan Province","award":["2021JJ20017"],"award-info":[{"award-number":["2021JJ20017"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Rel."],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1109\/tr.2022.3215243","type":"journal-article","created":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T00:40:19Z","timestamp":1667522419000},"page":"1029-1037","source":"Crossref","is-referenced-by-count":159,"title":["Data Augmentation and Intelligent Fault Diagnosis of Planetary Gearbox Using ILoFGAN Under Extremely Limited Samples"],"prefix":"10.1109","volume":"72","author":[{"given":"Mingzhi","family":"Chen","sequence":"first","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7106-0009","authenticated-orcid":false,"given":"Haidong","family":"Shao","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoxuan","family":"Dou","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8735-6787","authenticated-orcid":false,"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3946-8124","authenticated-orcid":false,"given":"Bin","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Management Science, University of Strathclyde, Glasgow, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1613\/jair.1.11192"},{"key":"ref35","first-page":"1398","article-title":"Multiscale structural similarity for image quality assessment","author":"zhou","year":"2003","journal-title":"Proc 37th Asilomar Conf Signals Syst Comput"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2013.12.003"},{"key":"ref34","article-title":"GANs trained by a two time-scale update rule converge to a local nash equilibrium","author":"heusel","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref14","first-page":"1322","article-title":"ADASYN: Adaptive synthetic sampling approach for imbalanced learning","author":"he","year":"2008","journal-title":"Proc IEEE Int Joint Conf Neural Netw"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: From error visibility to structural similarity","volume":"13","author":"zhou","year":"2004","journal-title":"IEEE Trans Image Process"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.03.091"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00835"},{"key":"ref11","doi-asserted-by":"crossref","DOI":"10.1186\/s40537-019-0197-0","article-title":"A survey on image data augmentation for deep learning","volume":"6","author":"shorten","year":"2019","journal-title":"J Big Data"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2864759"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3125385"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2837621"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2021.3117732"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2019.2896240"},{"key":"ref17","first-page":"5769","article-title":"Improved training of wasserstein GANs","volume":"30","author":"gulrajani","year":"2017","journal-title":"Proc 31st Annu Conf Neural Inf Process Syst"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref16","first-page":"214","article-title":"Wasserstein generative adversarial networks","author":"arjovsky","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref38","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017"},{"key":"ref19","first-page":"2642","article-title":"Conditional image synthesis with auxiliary classifier GANs","volume":"70","author":"odena","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref18","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2924003"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1177\/0954407020923258"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CAC51589.2020.9327104"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2021.109467"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2020.108371"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/ab3072"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.compind.2019.01.001"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3082264"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2020.3009343"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3127636"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.37965\/jdmd.2022.68"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2019.2956120"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2019.107377"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMECH.2021.3058061"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105313"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2021.3090310"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.37965\/jdmd.2022.53"}],"container-title":["IEEE Transactions on Reliability"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/24\/10236915\/09931615.pdf?arnumber=9931615","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T18:17:19Z","timestamp":1695665839000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9931615\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":39,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tr.2022.3215243","relation":{},"ISSN":["0018-9529","1558-1721"],"issn-type":[{"value":"0018-9529","type":"print"},{"value":"1558-1721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9]]}}}