{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T15:55:17Z","timestamp":1780674917305,"version":"3.54.1"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":["62125205"],"award-info":[{"award-number":["62125205"]}],"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":["U23A20303"],"award-info":[{"award-number":["U23A20303"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015401","name":"Key Research and Development Projects of Shaanxi Province","doi-asserted-by":"publisher","award":["2021ZDLGYO5-04"],"award-info":[{"award-number":["2021ZDLGYO5-04"]}],"id":[{"id":"10.13039\/501100015401","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tmm.2024.3521722","type":"journal-article","created":{"date-parts":[[2024,12,24]],"date-time":"2024-12-24T19:21:58Z","timestamp":1735068118000},"page":"597-609","source":"Crossref","is-referenced-by-count":3,"title":["Combating Noisy Labels by Alleviating the Memorization of DNNs to Noisy Labels"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1874-9792","authenticated-orcid":false,"given":"Shunjie","family":"Yuan","sequence":"first","affiliation":[{"name":"State Key Laboratory of Integrated Services Networks, and the School of Cyber Engineering, Xidian University, Xi&#x0027;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5583-4155","authenticated-orcid":false,"given":"Xinghua","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Integrated Services Networks, and the School of Cyber Engineering, Xidian University, Xi&#x0027;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5437-3572","authenticated-orcid":false,"given":"Yinbin","family":"Miao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Integrated Services Networks, and the School of Cyber Engineering, Xidian University, Xi&#x0027;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5647-0958","authenticated-orcid":false,"given":"Haiyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Integrated Services Networks, and the School of Cyber Engineering, Xidian University, Xi&#x0027;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4238-3295","authenticated-orcid":false,"given":"Ximeng","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3491-8146","authenticated-orcid":false,"given":"Robert H.","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Information Systems, Singapore Management University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3531013"},{"key":"ref4","article-title":"FHA-kitchens: A novel dataset for fine-grained hand action recognition in kitchen scenes","author":"Zhe","year":"2023"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1031"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.897"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3096200"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3032227"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3235381"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3177942"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3233\/978-1-61499-098-7-870"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-13453-2_1"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118101"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.4135\/9781071810118"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/792538.792543"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-013-5412-1"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_5"},{"key":"ref19","first-page":"2069","article-title":"Diverse sequential subset selection for supervised video summarization","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Gong","year":"2014"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_24"},{"key":"ref21","first-page":"6448","article-title":"Does label smoothing mitigate label noise?","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lukasik","year":"2020"},{"key":"ref22","first-page":"17044","article-title":"Identifying mislabeled data using the area under the margin ranking","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Pleiss","year":"2020"},{"key":"ref23","article-title":"Generalized cross entropy loss for training deep neural networks with noisy labels","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Zhang","year":"2018"},{"key":"ref24","article-title":"Sample selection with uncertainty of losses for learning with noisy labels","volume-title":"Proc. 10th Int. Conf. Learn. Representations","author":"Xia","year":"2022"},{"key":"ref25","first-page":"7164","article-title":"How does disagreement help generalization against label corruption?","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yu","year":"2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3115635"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01374"},{"key":"ref28","first-page":"21382","article-title":"A topological filter for learning with label noise","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Wu","year":"2020"},{"key":"ref29","article-title":"DivideMix: Learning with noisy labels as semi-supervised learning","volume-title":"Proc. 8th Int. Conf. Learn. Representations","author":"Li","year":"2020"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3119861"},{"key":"ref31","first-page":"24392","article-title":"Understanding and improving early stopping for learning with noisy labels","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Bai","year":"2021"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00044"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20053-3_8"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00945"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3338268"},{"key":"ref36","article-title":"Robust early-learning: Hindering the memorization of noisy labels","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xia","year":"2021"},{"key":"ref37","article-title":"Training convolutional networks with noisy labels","author":"Sukhbaatar","year":"2014"},{"key":"ref38","article-title":"Training deep neural-networks using a noise adaptation layer","author":"Goldberger","year":"2017","journal-title":"Proc. 5th Int. Conf. Learn. Representations"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.240"},{"key":"ref40","article-title":"Using trusted data to train deep networks on labels corrupted by severe noise","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Hendrycks","year":"2018"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00019"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00932"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00013"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109013"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109121"},{"key":"ref46","first-page":"5050","article-title":"MixMatch: A holistic approach to semi-supervised learning","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Berthelot","year":"2019"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2005.10.028"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"},{"key":"ref49","article-title":"Temporal ensembling for semi-supervised learning","volume-title":"Proc. 5th Int. Conf. Learn. Representations","author":"Laine","year":"2017"},{"key":"ref50","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Tarvainen","year":"2017"},{"key":"ref51","first-page":"1","article-title":"MixUp: Beyond empirical risk minimization","volume-title":"Proc. 6th Int. Conf. Learn. Representations","author":"Zhang","year":"2018"},{"key":"ref52","first-page":"596","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","volume":"33","author":"Sohn","year":"2020"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20056-4_39"},{"key":"ref54","article-title":"FreeMatch: Self-adaptive thresholding for semi-supervised learning","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Wang","year":"2023"},{"key":"ref55","first-page":"1163","article-title":"Regularization with stochastic transformations and perturbations for deep semi-supervised learning","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Sajjadi","year":"2016"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01553"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298885"},{"key":"ref58","first-page":"10","article-title":"Learning with symmetric label noise: The importance of being unhinged","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Rooyen","year":"2015"},{"key":"ref59","first-page":"233","article-title":"A closer look at memorization in deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arpit","year":"2017"},{"key":"ref60","article-title":"Training deep neural networks on noisy labels with bootstrapping","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Reed","year":"2015"},{"key":"ref61","first-page":"960","article-title":"Decoupling when to update from how to update","volume-title":"Proc. Proc. 31st Annu. Conf. Neural Inf. Process. Syst.","author":"Malach","year":"2017"},{"key":"ref62","first-page":"2304","article-title":"MentorNet: Learning data-driven curriculum for very deep neural networks on corrupted labels","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Jiang","year":"2018"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00906"},{"key":"ref64","first-page":"3763","article-title":"Robust inference via generative classifiers for handling noisy labels","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lee","year":"2019"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00718"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00041"},{"key":"ref67","first-page":"20331","article-title":"Early-learning regularization prevents memorization of noisy labels","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Liu","year":"2020"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00935"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6046\/10844992\/10814968.pdf?arnumber=10814968","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T18:39:40Z","timestamp":1740422380000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10814968\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":68,"URL":"https:\/\/doi.org\/10.1109\/tmm.2024.3521722","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}