{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T18:58:50Z","timestamp":1789498730105,"version":"build-2803163510"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100018537","name":"National Science and Technology Major Project","doi-asserted-by":"publisher","award":["2021ZD0111601"],"award-info":[{"award-number":["2021ZD0111601"]}],"id":[{"id":"10.13039\/501100018537","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206060"],"award-info":[{"award-number":["62206060"]}],"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":["62206314"],"award-info":[{"award-number":["62206314"]}],"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":["62325605"],"award-info":[{"award-number":["62325605"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangzhou Basic and Applied Basic Research Foundation","award":["SL2022A04J01626"],"award-info":[{"award-number":["SL2022A04J01626"]}]},{"name":"Guangzhou Basic and Applied Basic Research Foundation","award":["2022A1515011835"],"award-info":[{"award-number":["2022A1515011835"]}]},{"name":"Guangzhou Basic and Applied Basic Research Foundation","award":["2023A1515012561"],"award-info":[{"award-number":["2023A1515012561"]}]},{"name":"Science and Technology Projects in Guangzhou","award":["2024A04J4388"],"award-info":[{"award-number":["2024A04J4388"]}]},{"name":"Guangdong Provincial Key Laboratory of Intellectual Property and Big Data","award":["2018B030322016"],"award-info":[{"award-number":["2018B030322016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tip.2024.3448248","type":"journal-article","created":{"date-parts":[[2024,9,2]],"date-time":"2024-09-02T14:03:50Z","timestamp":1725285830000},"page":"4811-4823","source":"Crossref","is-referenced-by-count":19,"title":["Dynamic Correlation Learning and Regularization for Multi-Label Confidence Calibration"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5848-5624","authenticated-orcid":false,"given":"Tianshui","family":"Chen","sequence":"first","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4504-4441","authenticated-orcid":false,"given":"Weihang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9564-8288","authenticated-orcid":false,"given":"Tao","family":"Pu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0663-199X","authenticated-orcid":false,"given":"Jinghui","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8336-5109","authenticated-orcid":false,"given":"Zhijing","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Science, North China University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2248-3755","authenticated-orcid":false,"given":"Liang","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref2","first-page":"1","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Dosovitskiy"},{"key":"ref3","first-page":"15288","article-title":"Calibrating deep neural networks using focal loss","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Mukhoti"},{"key":"ref4","first-page":"1321","article-title":"On calibration of modern neural networks","volume-title":"Proc. 34th Intl. Conf. Mach. Learn.","author":"Guo"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3282070"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/rob.21918"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1561\/0600000079"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2011-000291"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788613"},{"key":"ref10","first-page":"1","article-title":"When does label smoothing help?","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"M\u00fcller"},{"key":"ref11","article-title":"Improved trainable calibration method for neural networks on medical imaging classification","author":"Liang","year":"2020","journal-title":"arXiv:2009.04057"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2491929"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3148867"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3266161"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00061"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00532"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58589-1_39"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01621"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3047335"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01561"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00018"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1182"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9602"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.2307\/2987588"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-024-02127-2"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-021-11818-8"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3025814"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01027"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123526"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3003779"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.37"},{"key":"ref32","article-title":"Multiple object recognition with visual attention","author":"Ba","year":"2014","journal-title":"arXiv:1412.7755"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12281"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.58"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.251"},{"key":"ref36","first-page":"1","article-title":"Gated graph sequence neural networks","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Li"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3131222"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.107920"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17098"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref42","first-page":"2805","article-title":"Trainable calibration measures for neural networks from kernel mean embeddings","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","volume":"80","author":"Kumar"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3380250"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3388094"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.3390\/e19070313"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i1.19910"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-016-0981-7"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.219"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/2812802"},{"issue":"7","key":"ref53","first-page":"1","article-title":"Measuring calibration in deep learning","volume-title":"Proc. CVPR Workshops","volume":"2","author":"Nixon"},{"key":"ref54","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/83\/10346232\/10663362.pdf?arnumber=10663362","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T00:03:18Z","timestamp":1725753798000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10663362\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/tip.2024.3448248","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}