{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T18:09:03Z","timestamp":1776276543201,"version":"3.50.1"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"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":["62020106004"],"award-info":[{"award-number":["62020106004"]}],"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":["92048301"],"award-info":[{"award-number":["92048301"]}],"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":["61906133"],"award-info":[{"award-number":["61906133"]}],"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":["61703304"],"award-info":[{"award-number":["61703304"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004712","name":"Opening Foundation of Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, China","doi-asserted-by":"publisher","award":["TJUT-KLICNST-K20180002"],"award-info":[{"award-number":["TJUT-KLICNST-K20180002"]}],"id":[{"id":"10.13039\/501100004712","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1109\/tnnls.2021.3102514","type":"journal-article","created":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T19:55:00Z","timestamp":1628798100000},"page":"2558-2570","source":"Crossref","is-referenced-by-count":75,"title":["A Novel Deep Class-Imbalanced Semisupervised Model for Wind Turbine Blade Icing Detection"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5336-7952","authenticated-orcid":false,"given":"Xu","family":"Cheng","sequence":"first","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2074-0228","authenticated-orcid":false,"given":"Fan","family":"Shi","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5133-6688","authenticated-orcid":false,"given":"Xiufeng","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Technology, Management and Economics, Technical University of Denmark, Kongens Lyngby, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5060-9223","authenticated-orcid":false,"given":"Meng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6705-3831","authenticated-orcid":false,"given":"Shengyong","family":"Chen","sequence":"additional","affiliation":[{"name":"Engineering Research Center of Learning-Based Intelligent System, Ministry of Education, Tianjin, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jweia.2017.11.024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2017.10.074"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/we.2427"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TSTE.2012.2194725"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.coldregions.2010.01.005"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2016.06.080"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2019.03.112"},{"key":"ref8","article-title":"WaveletAE: A wavelet-enhanced autoencoder for wind turbine blade icing detection","author":"Yuan","year":"2019","journal-title":"arXiv:1902.05625"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.coldregions.2018.10.009"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2009.07.028"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jweia.2018.01.043"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2020.2967115"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2018.08.050"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/en11102548"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1002\/ese3.449"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2844805"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3358162"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jallcom.2019.06.241"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.apsusc.2012.07.118"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2016.06.064"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2017.06.045"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ECC.2016.7810494"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3439950"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335388"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220042"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330871"},{"key":"ref28","article-title":"Deep semi-supervised anomaly detection","author":"Ruff","year":"2019","journal-title":"arXiv:1906.02694"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2010.06.005"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.72"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-015-0441-y"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2651018"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-015-4478-2"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.04.014"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794069"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-017-1090-9"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2018.03.015"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487633"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-38658-9_39"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-04717-1_8"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6165"},{"key":"ref42","first-page":"3235","article-title":"Realistic evaluation of deep semi-supervised learning algorithms","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Oliver"},{"key":"ref43","first-page":"1","article-title":"Semi-supervised learning for imbalanced sentiment classification","volume-title":"Proc. 22nd Int. Joint Conf. Artif. Intell.","author":"Li"},{"key":"ref44","first-page":"131","article-title":"Semi-supervised self-training approaches for imbalanced splice site datasets","volume-title":"Proc. 6th Int. Conf. Bioinf. Comput. Biol. (BICoB)","author":"Stanescu"},{"key":"ref45","first-page":"1","article-title":"Rethinking the value of labels for improving class-imbalanced learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Yang"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/MIPR.2018.00027"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.07.011"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00949"},{"key":"ref50","first-page":"1567","article-title":"Learning imbalanced datasets with label-distribution-aware margin loss","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Cao"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref52","first-page":"4077","article-title":"Prototypical networks for few-shot learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Snell"},{"key":"ref53","first-page":"1","article-title":"Max-margin class imbalanced learning with Gaussian affinity","volume-title":"Proc. ICCV","author":"Hayat"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966039"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9786556\/09512275.pdf?arnumber=9512275","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T22:59:02Z","timestamp":1705013942000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9512275\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6]]},"references-count":55,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2021.3102514","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6]]}}}