{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:01:47Z","timestamp":1752192107797,"version":"3.41.2"},"reference-count":37,"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, China","doi-asserted-by":"publisher","award":["62303201","62303404","62171476"],"award-info":[{"award-number":["62303201","62303404","62171476"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Yunnan Fundamental Research Projects, China","award":["202401CF070111","202401CF070171","202301BE070001-049"],"award-info":[{"award-number":["202401CF070111","202401CF070171","202301BE070001-049"]}]},{"name":"Key Program of the National Natural Science Foundation of China, China","award":["62233018"],"award-info":[{"award-number":["62233018"]}]},{"name":"Yunnan Xing Dian Talents Plan Young Program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Instrum. Meas."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tim.2025.3580794","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T13:37:33Z","timestamp":1750253853000},"page":"1-10","source":"Crossref","is-referenced-by-count":0,"title":["Data-Efficient Soft Sensing Learning for Flotation Process Monitoring"],"prefix":"10.1109","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7574-2808","authenticated-orcid":false,"given":"Jin","family":"Zhang","sequence":"first","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0284-2995","authenticated-orcid":false,"given":"Mingxi","family":"Ai","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Yunnan University, Kunming, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4132-4987","authenticated-orcid":false,"given":"Zhaohui","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2060-6574","authenticated-orcid":false,"given":"Yongfang","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Automation, Central South University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2780-4925","authenticated-orcid":false,"given":"Jiande","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Engineering, Yunnan Key Laboratory of Intelligent Systems and Computing, Yunnan University, Kunming, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7531-7833","authenticated-orcid":false,"given":"Jun","family":"Ma","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/tim.2025.3554879"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2020.08.024"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2022.3206696"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2021.3124015"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2023.103004"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2023.3311070"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.mineng.2017.10.005"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2021.1894366"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.mineng.2021.107344"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2022.09.250"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-022-01723-4"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2023.3290352"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3275071"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.5555\/3495724.3497510"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00203"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58621-8_45"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681600"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2024.3465597"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.powtec.2024.119866"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2022.11.004"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2969709"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2023.3295852"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.mineng.2023.108179"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3227553"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2025.3527581"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2020.3004382"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2020.104360"},{"key":"ref31","first-page":"801","article-title":"Statistical analysis of semi-supervised regression","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lafferty"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2025.3548053"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.minpro.2006.10.009"},{"key":"ref34","first-page":"1","article-title":"FreeMatch: Self-adaptive thresholding for semi-supervised learning","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Wang"},{"key":"ref35","first-page":"5050","article-title":"MixMatch: A holistic approach to semi-supervised learning","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Berthelot"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-04083-1"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2023.3342458"}],"container-title":["IEEE Transactions on Instrumentation and Measurement"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/19\/10764799\/11040022.pdf?arnumber=11040022","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T05:13:45Z","timestamp":1752124425000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11040022\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/tim.2025.3580794","relation":{},"ISSN":["0018-9456","1557-9662"],"issn-type":[{"type":"print","value":"0018-9456"},{"type":"electronic","value":"1557-9662"}],"subject":[],"published":{"date-parts":[[2025]]}}}