{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T21:46:38Z","timestamp":1762033598075,"version":"3.37.3"},"reference-count":30,"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"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61402100"],"award-info":[{"award-number":["61402100"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2904536","type":"journal-article","created":{"date-parts":[[2019,3,12]],"date-time":"2019-03-12T22:31:30Z","timestamp":1552429890000},"page":"34499-34507","source":"Crossref","is-referenced-by-count":11,"title":["A Multi-Task Learning Model for Better Representation of Clothing Images"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0313-8833","authenticated-orcid":false,"given":"Cairong","family":"Yan","sequence":"first","affiliation":[]},{"given":"Lingjie","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Yongquan","family":"Wan","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"Generalized K-fan multimodal deep model with shared representations","year":"2015","author":"chen","key":"ref30"},{"key":"ref10","first-page":"1","article-title":"Learning graph representations with recurrent neural network autoencoders","author":"taheri","year":"2018","journal-title":"Proc KDD Deep Learn Day"},{"key":"ref11","first-page":"91","article-title":"Towards better understanding the clothing fashion styles: A multimodal deep learning approach","author":"ma","year":"2004","journal-title":"Proc AAAI"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.451"},{"key":"ref13","first-page":"1216","article-title":"Learning to appreciate the aesthetic effects of clothing","author":"jia","year":"2016","journal-title":"Proc AAAI"},{"journal-title":"Fashioning with networks Neural style transfer to design clothes","year":"2017","author":"date","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2984511.2984573"},{"key":"ref16","first-page":"2853","article-title":"The benefit of multi-task representation learning","volume":"17","author":"maurer","year":"2013","journal-title":"J Mach Learn Res"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01424-7_27"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2014.2307227"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2016.2639323"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123441"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"ImageNet classification with deep convolutional neural networks","volume":"60","author":"krizhevsky","year":"2012","journal-title":"Commun ACM"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298688"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00067"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.5244\/C.2.23"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390177"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489105"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2869884"},{"key":"ref24","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proc AISTATS"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2012.02.049"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248101"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01258-8_5"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08666119.pdf?arnumber=8666119","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T19:40:48Z","timestamp":1628624448000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8666119\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2904536","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}