{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T21:10:59Z","timestamp":1777497059230,"version":"3.51.4"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Key Program of the Ministry of Science and Technology","award":["2018YFB1702703"],"award-info":[{"award-number":["2018YFB1702703"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Circuits Syst. Video Technol."],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1109\/tcsvt.2021.3139968","type":"journal-article","created":{"date-parts":[[2021,12,31]],"date-time":"2021-12-31T20:46:54Z","timestamp":1640983614000},"page":"4953-4967","source":"Crossref","is-referenced-by-count":22,"title":["Partial Label Learning Based on Disambiguation Correction Net With Graph Representation"],"prefix":"10.1109","volume":"32","author":[{"given":"Jinfu","family":"Fan","sequence":"first","affiliation":[{"name":"Department of Control Science and Engineering, College of Electronics and Information Engineering, Tongji University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2415-8844","authenticated-orcid":false,"given":"Yang","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Control Science and Engineering, College of Electronics and Information Engineering, Tongji University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4925-2941","authenticated-orcid":false,"given":"Zhongjie","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Control Science and Engineering, College of Electronics and Information Engineering, Tongji University, Shanghai, China"}]},{"given":"Jinyi","family":"Gu","sequence":"additional","affiliation":[{"name":"Department of Control Science and Engineering, College of Electronics and Information Engineering, Tongji University, Shanghai, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/318"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.52"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.97"},{"key":"ref4","first-page":"1629","article-title":"Learnability of the superset label learning problem","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Liu"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2015.2497270"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2008.07.014"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2010.2058470"},{"key":"ref8","first-page":"1504","article-title":"Learning from candidate labeling sets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"23","author":"Luo"},{"key":"ref9","first-page":"548","article-title":"A conditional multinomial mixture model for superset label learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"25","author":"Liu"},{"key":"ref10","first-page":"1501","article-title":"Learning from partial labels","volume":"12","author":"Cour","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-2006-10503"},{"key":"ref12","first-page":"4048","article-title":"Solving the partial label learning problem: An instance-based approach","volume-title":"Proc. IJCAI","author":"Zhang"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939788"},{"key":"ref14","first-page":"137","article-title":"Who\u2019s in the picture","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Berg"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401958"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2933837"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013542"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2721942"},{"key":"ref19","article-title":"Graph convolutional matrix completion","volume-title":"arXiv:1706.02263","author":"Van Den Berg","year":"2017"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2433396.2433471"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref22","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hamilton"},{"key":"ref23","article-title":"GraphSAINT: Graph sampling based inductive learning method","volume-title":"arXiv:1907.04931","author":"Zeng","year":"2019"},{"key":"ref24","first-page":"1","article-title":"Co-teaching: Robust training of deep neural networks with extremely noisy labels","volume-title":"Proc. NeurIPS","author":"Han"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-016-5606-4"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330840"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6621"},{"key":"ref28","first-page":"6500","article-title":"Progressive identification of true labels for partial-label learning","volume-title":"Proc. ICML","author":"Lv"},{"key":"ref29","first-page":"1","article-title":"Leveraged weighted loss for partial label learning","volume-title":"Proc. IEEE Int. Conf. Multimedia Expo (ICME)","author":"Wen"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICME51207.2021.9428103"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/398"},{"key":"ref32","first-page":"1","article-title":"Spectral networks and locally connected networks on graphs","volume":"abs\/1312.6203","author":"Bruna","year":"2014","journal-title":"CoRR"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3058098"},{"key":"ref34","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume":"abs\/1609.02907","author":"Kipf","year":"2017","journal-title":"CoRR"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3067062"},{"key":"ref36","first-page":"1025","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. NIPS","author":"Hamilton"},{"key":"ref37","article-title":"GraphSAINT: Graph sampling based inductive learning method","volume-title":"arXiv:1907.04931","author":"Zeng","year":"2019"},{"key":"ref38","first-page":"5453","article-title":"Representation learning on graphs with jumping knowledge networks","volume-title":"Proc. ICML","author":"Xu"},{"key":"ref39","volume-title":"UCI machine learning repository","author":"Dua","year":"2019"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-16181-5_56"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2690144"}],"container-title":["IEEE Transactions on Circuits and Systems for Video Technology"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/76\/9849156\/09667361.pdf?arnumber=9667361","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,13]],"date-time":"2024-01-13T21:44:36Z","timestamp":1705182276000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9667361\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":41,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tcsvt.2021.3139968","relation":{},"ISSN":["1051-8215","1558-2205"],"issn-type":[{"value":"1051-8215","type":"print"},{"value":"1558-2205","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8]]}}}