{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T06:30:33Z","timestamp":1745389833480,"version":"3.37.3"},"reference-count":41,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004921","name":"Shanghai Jiao Tong University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004921","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1016\/j.patcog.2022.108777","type":"journal-article","created":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T08:09:04Z","timestamp":1652256544000},"page":"108777","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":126,"special_numbering":"C","title":["DMT: Dynamic mutual training for semi-supervised learning"],"prefix":"10.1016","volume":"130","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9096-6877","authenticated-orcid":false,"given":"Zhengyang","family":"Feng","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5331-050X","authenticated-orcid":false,"given":"Qianyu","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Qiqi","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Guangliang","family":"Cheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0959-408X","authenticated-orcid":false,"given":"Xuequan","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Jianping","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Lizhuang","family":"Ma","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2022.108777_sbref0001","series-title":"British Machine Vision Conference","article-title":"Wide residual networks","author":"Zagoruyko","year":"2016"},{"key":"10.1016\/j.patcog.2022.108777_bib0002","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.patcog.2019.01.006","article-title":"Wider or deeper: revisiting the resnet model for visual recognition","volume":"90","author":"Wu","year":"2019","journal-title":"Pattern Recognit."},{"issue":"4","key":"10.1016\/j.patcog.2022.108777_bib0003","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","article-title":"DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs","volume":"40","author":"Chen","year":"2017","journal-title":"Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.patcog.2022.108777_bib0004","series-title":"Computer Vision and Pattern Recognition","first-page":"2881","article-title":"Pyramid scene parsing network","author":"Zhao","year":"2017"},{"key":"10.1016\/j.patcog.2022.108777_bib0005","series-title":"Computer Vision and Pattern Recognition","first-page":"3213","article-title":"The cityscapes dataset for semantic urban scene understanding","author":"Cordts","year":"2016"},{"key":"10.1016\/j.patcog.2022.108777_bib0006","series-title":"Annual Meeting of the Association for Computational Linguistics","first-page":"189","article-title":"Unsupervised word sense disambiguation rivaling supervised methods","author":"Yarowsky","year":"1995"},{"key":"10.1016\/j.patcog.2022.108777_sbref0007","series-title":"International Conference on Machine Learning workshop","article-title":"Pseudo-Label: the simple and efficient semi-supervised learning method for deep neural networks","author":"Lee","year":"2013"},{"key":"10.1016\/j.patcog.2022.108777_bib0008","series-title":"British Machine Vision Conference","first-page":"65","article-title":"Adversarial learning for semi-supervised semantic segmentation","author":"Hung","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_bib0009","series-title":"Neural Information Processing Systems","first-page":"1195","article-title":"Mean teachers are better role models: weight-averaged consistency targets improve semi-supervised deep learning results","author":"Tarvainen","year":"2017"},{"key":"10.1016\/j.patcog.2022.108777_sbref0010","series-title":"British Machine Vision Conference","article-title":"Semi-supervised semantic segmentation needs strong, varied perturbations","author":"French","year":"2020"},{"key":"10.1016\/j.patcog.2022.108777_bib0011","series-title":"Neural Information Processing Systems","first-page":"5050","article-title":"MixMatch: a holistic approach to semi-supervised learning","author":"Berthelot","year":"2019"},{"key":"10.1016\/j.patcog.2022.108777_sbref0012","series-title":"Pattern Analysis and Machine Intelligence","article-title":"Semi-supervised semantic segmentation with high- and low-level consistency","author":"Mittal","year":"2019"},{"key":"10.1016\/j.patcog.2022.108777_bib0013","series-title":"European Conference on Computer Vision","first-page":"289","article-title":"Unsupervised domain adaptation for semantic segmentation via class-balanced self-training","author":"Zou","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_bib0014","series-title":"International Conference on Machine Learning","first-page":"41","article-title":"Curriculum learning","author":"Bengio","year":"2009"},{"key":"10.1016\/j.patcog.2022.108777_sbref0015","series-title":"AAAI Conference on Artificial Intelligence","article-title":"Curriculum labeling: revisiting pseudo-labeling for semi-supervised learning","author":"Cascante-Bonilla","year":"2021"},{"key":"10.1016\/j.patcog.2022.108777_sbref0016","series-title":"Computer Vision and Pattern Recognition","article-title":"Semi-supervised semantic segmentation with cross-consistency training","author":"Ouali","year":"2020"},{"key":"10.1016\/j.patcog.2022.108777_bib0017","series-title":"European Conference on Computer Vision","first-page":"135","article-title":"Deep co-training for semi-supervised image recognition","author":"Qiao","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_bib0018","doi-asserted-by":"crossref","first-page":"107269","DOI":"10.1016\/j.patcog.2020.107269","article-title":"Deep co-training for semi-supervised image segmentation","volume":"107","author":"Peng","year":"2020","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2022.108777_bib0019","series-title":"International Conference on Computer Vision","first-page":"6728","article-title":"Dual student: breaking the limits of the teacher in semi-supervised learning","author":"Ke","year":"2019"},{"issue":"3","key":"10.1016\/j.patcog.2022.108777_bib0020","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1007\/s10115-009-0209-z","article-title":"Semi-supervised learning by disagreement","volume":"24","author":"Zhou","year":"2010","journal-title":"Knowl. Inf. Syst."},{"key":"10.1016\/j.patcog.2022.108777_sbref0021","series-title":"International Conference on Machine Learning","article-title":"How does disagreement help generalization against label corruption?","author":"Yu","year":"2019"},{"key":"10.1016\/j.patcog.2022.108777_bib0022","series-title":"European Conference on Computer Vision","first-page":"6","article-title":"Guided collaborative training for pixel-wise semi-supervised learning","volume":"vol.\u00a02","author":"Ke","year":"2020"},{"issue":"4","key":"10.1016\/j.patcog.2022.108777_bib0023","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/BF00116829","article-title":"Learning from noisy examples","volume":"2","author":"Angluin","year":"1988","journal-title":"Mach. Learn."},{"key":"10.1016\/j.patcog.2022.108777_sbref0024","series-title":"International Conference on Learning Representations","article-title":"Training deep neural-networks using a noise adaptation layer","author":"Goldberger","year":"2017"},{"key":"10.1016\/j.patcog.2022.108777_bib0025","series-title":"Neural Information Processing Systems","first-page":"960","article-title":"Decoupling \u201cwhen to update\u201d from \u201chow to update\u201d","author":"Malach","year":"2017"},{"key":"10.1016\/j.patcog.2022.108777_bib0026","series-title":"Neural Information Processing Systems","first-page":"8527","article-title":"Co-teaching: robust training of deep neural networks with extremely noisy labels","author":"Han","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_bib0027","series-title":"Computer Vision and Pattern Recognition","first-page":"13400","article-title":"Density-aware graph for deep semi-supervised visual recognition","author":"Li","year":"2020"},{"key":"10.1016\/j.patcog.2022.108777_bib0028","series-title":"Neural Information Processing Systems","first-page":"529","article-title":"Semi-supervised learning by entropy minimization","author":"Grandvalet","year":"2005"},{"key":"10.1016\/j.patcog.2022.108777_sbref0029","series-title":"International Conference on Learning Representations","article-title":"ReMixMatch: semi-supervised learning with distribution alignment and augmentation anchoring","author":"Berthelot","year":"2020"},{"key":"10.1016\/j.patcog.2022.108777_sbref0030","series-title":"International Conference on Learning Representations","article-title":"Temporal ensembling for semi-supervised learning","author":"Laine","year":"2017"},{"key":"10.1016\/j.patcog.2022.108777_bib0031","series-title":"International Conference on Computer Vision","first-page":"5982","article-title":"Confidence regularized self-training","author":"Zou","year":"2019"},{"key":"10.1016\/j.patcog.2022.108777_bib0032","series-title":"Technical Report","article-title":"Learning Multiple Layers of Features from Tiny Images","author":"Krizhevsky","year":"2009"},{"issue":"1","key":"10.1016\/j.patcog.2022.108777_bib0033","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1007\/s11263-014-0733-5","article-title":"The pascal visual object classes challenge: A retrospective","volume":"111","author":"Everingham","year":"2015","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.patcog.2022.108777_bib0034","series-title":"Neural Information Processing Systems","first-page":"3235","article-title":"Realistic evaluation of deep semi-supervised learning algorithms","author":"Oliver","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_bib0035","series-title":"International Conference on Computer Vision","first-page":"991","article-title":"Semantic contours from inverse detectors","author":"Hariharan","year":"2011"},{"key":"10.1016\/j.patcog.2022.108777_sbref0036","series-title":"International Conference on Learning Representations","article-title":"Mixed precision training","author":"Micikevicius","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_sbref0037","series-title":"Conference on Uncertainty in Artificial Intelligence","article-title":"Averaging weights leads to wider optima and better generalization","author":"Izmailov","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_bib0038","series-title":"Computer Vision and Pattern Recognition workshop","first-page":"702","article-title":"RandAugment: practical automated data augmentation with a reduced search space","author":"Cubuk","year":"2020"},{"key":"10.1016\/j.patcog.2022.108777_sbref0039","series-title":"International Conference on Learning Representations","article-title":"mixup: Beyond empirical risk minimization","author":"Zhang","year":"2018"},{"key":"10.1016\/j.patcog.2022.108777_bib0040","series-title":"International Conference on Computer Vision","first-page":"1476","article-title":"S4L: self-supervised semi-supervised learning","author":"Zhai","year":"2019"},{"key":"10.1016\/j.patcog.2022.108777_bib41","doi-asserted-by":"crossref","first-page":"9085","DOI":"10.1109\/TIP.2021.3122004","article-title":"Night-time scene parsing with a Large real dataset","volume":"30","author":"Tan","year":"2021","journal-title":"IEEE Trans. Image proc."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320322002588?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320322002588?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T11:00:56Z","timestamp":1672398056000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320322002588"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10]]},"references-count":41,"alternative-id":["S0031320322002588"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2022.108777","relation":{},"ISSN":["0031-3203"],"issn-type":[{"type":"print","value":"0031-3203"}],"subject":[],"published":{"date-parts":[[2022,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"DMT: Dynamic mutual training for semi-supervised learning","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2022.108777","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"108777"}}