{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T14:15:25Z","timestamp":1774361725418,"version":"3.50.1"},"reference-count":31,"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:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61473201"],"award-info":[{"award-number":["61473201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772576"],"award-info":[{"award-number":["61772576"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"crossref","award":["2018YFB1309200"],"award-info":[{"award-number":["2018YFB1309200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2946062","type":"journal-article","created":{"date-parts":[[2019,10,7]],"date-time":"2019-10-07T19:55:56Z","timestamp":1570478156000},"page":"148413-148423","source":"Crossref","is-referenced-by-count":23,"title":["Defect Enhancement Generative Adversarial Network for Enlarging Data Set of Microcrack Defect"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7743-4160","authenticated-orcid":false,"given":"Song","family":"Lin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7041-8934","authenticated-orcid":false,"given":"Zhiyong","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lining","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2016.2520955"},{"key":"ref30","article-title":"Energy-based generative adversarial network","author":"zhao","year":"2016","journal-title":"arXiv 1609 03126"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68345-4_17"},{"key":"ref11","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref12","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","volume":"abs 1409 1556","author":"simonyan","year":"2014","journal-title":"CoRR"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/S0957-4174(98)00079-7"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2011.02.002"},{"key":"ref18","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","first-page":"1060","article-title":"Generative adversarial text to image synthesis","author":"reed","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref28","first-page":"5767","article-title":"Improved training of wasserstein GANs","author":"gulrajani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.12.032"},{"key":"ref27","first-page":"1","article-title":"Wasserstein GAN","volume":"abs 1701 7875","author":"arjovsky","year":"2017","journal-title":"CoRR"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/app8112195"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1016\/j.patcog.2011.07.025","article-title":"Wavelet-based defect detection in solar wafer images with inhomogeneous texture","volume":"45","author":"li","year":"2012","journal-title":"Pattern Recognit"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2885684"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICIT.2005.1600745"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1108\/IJCST-02-2014-0028"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2013.05.004"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1111\/mice.12353"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/s18041000"},{"key":"ref20","first-page":"613","article-title":"Generating videos with scene dynamics","author":"vondrick","year":"2016","journal-title":"Proc Conf Adv Neural Inf Process Syst"},{"key":"ref22","article-title":"SeqGAN: Sequence generative adversarial nets with policy gradient","author":"yu","year":"2016","journal-title":"arXiv 1609 05473"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1230"},{"key":"ref24","first-page":"1","article-title":"Conditional generative adversarial nets","volume":"abs 1411 1784","author":"mirza","year":"2014","journal-title":"CoRR"},{"key":"ref23","first-page":"1","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","volume":"abs 1511 6434","author":"radford","year":"2015","journal-title":"CoRR"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref25","first-page":"1486","article-title":"Deep generative image models using a Laplacian pyramid of adversarial networks","author":"denton","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08861335.pdf?arnumber=8861335","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T10:45:11Z","timestamp":1695293111000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8861335\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2946062","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}