{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T08:17:38Z","timestamp":1783671458932,"version":"3.55.0"},"reference-count":45,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing Municipality","doi-asserted-by":"publisher","award":["cstc2021jcyj-msxmX0066"],"award-info":[{"award-number":["cstc2021jcyj-msxmX0066"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012669","name":"Natural Science Foundation Project of Chongqing","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012669","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22274134"],"award-info":[{"award-number":["22274134"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.asoc.2026.115445","type":"journal-article","created":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T03:00:02Z","timestamp":1778814002000},"page":"115445","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["Multi-stage cost-efficient multi-label active learning"],"prefix":"10.1016","volume":"201","author":[{"given":"Yaling","family":"Ge","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunpeng","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoliang","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujia","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4353-1621","authenticated-orcid":false,"given":"Jun","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.asoc.2026.115445_bib0005","series-title":"European Conference on Computer Vision","first-page":"727","article-title":"Semi-supervised 3D object detection with proficient teachers","author":"Yin","year":"2022"},{"key":"10.1016\/j.asoc.2026.115445_bib0010","series-title":"International Conference on Machine Learning","first-page":"27075","article-title":"Hypertransformer: model generation for supervised and semi-supervised few-shot learning","author":"Zhmoginov","year":"2022"},{"key":"10.1016\/j.asoc.2026.115445_bib0015","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.ins.2022.10.066","article-title":"Cold-start active learning for image classification","volume":"616","author":"Jin","year":"2022","journal-title":"Inf. Sci."},{"issue":"11","key":"10.1016\/j.asoc.2026.115445_bib0020","doi-asserted-by":"crossref","first-page":"4754","DOI":"10.1109\/TFUZZ.2022.3159103","article-title":"C-loss based higher order fuzzy inference systems for identifying DNA N4-methylcytosine sites","volume":"30","author":"Ding","year":"2022","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"10.1016\/j.asoc.2026.115445_bib0025","series-title":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","first-page":"447","article-title":"Residual multilayer perceptrons for genotype-guided recurrence prediction of non-small cell lung cancer","author":"Ai","year":"2022"},{"key":"10.1016\/j.asoc.2026.115445_bib0030","series-title":"E3S Web of Conferences, 391","article-title":"The distributed deep learning paradigms for detection of weeds from crops in Indian agricultural farms","author":"Subbarayudu","year":"2023"},{"key":"10.1016\/j.asoc.2026.115445_bib0035","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1016\/j.ins.2022.05.070","article-title":"A novel myocardial infarction localization method using multi-branch DenseNet and spatial matching-based active semi-supervised learning","volume":"606","author":"He","year":"2022","journal-title":"Inf. Sci."},{"key":"10.1016\/j.asoc.2026.115445_bib0040","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.ins.2023.01.028","article-title":"Active learning for regression by inverse distance weighting","volume":"626","author":"Bemporad","year":"2023","journal-title":"Inf. Sci."},{"issue":"12","key":"10.1016\/j.asoc.2026.115445_bib0045","doi-asserted-by":"crossref","first-page":"9860","DOI":"10.1109\/TPAMI.2021.3136592","article-title":"Collaborative learning of label semantics and deep label-specific features for multi-label classification","volume":"44","author":"Hang","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"9","key":"10.1016\/j.asoc.2026.115445_bib0050","first-page":"5199","article-title":"Multi-label classification with label-specific feature generation: a wrapped approach","volume":"44","author":"Yu","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"10.1016\/j.asoc.2026.115445_bib0055","doi-asserted-by":"crossref","first-page":"2091","DOI":"10.1109\/TKDE.2020.3003899","article-title":"Cmal: cost-effective multi-label active learning by querying subexamples","volume":"34","author":"Yu","year":"2020","journal-title":"IEEE Trans. on Knowledge and Data Engineering"},{"issue":"12","key":"10.1016\/j.asoc.2026.115445_bib0060","doi-asserted-by":"crossref","first-page":"7177","DOI":"10.1002\/int.22585","article-title":"Cost-effective multi-instance multilabel active learning","volume":"36","author":"Su","year":"2021","journal-title":"Int. J. Intell. Syst."},{"key":"10.1016\/j.asoc.2026.115445_bib0065","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"14647","article-title":"Debiased learning from naturally imbalanced pseudo-labels","author":"Wang","year":"2022"},{"key":"10.1016\/j.asoc.2026.115445_bib0070","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"15099","article-title":"SimPLE: similar pseudo label exploitation for semi-supervised classification","author":"Hu","year":"2021"},{"key":"10.1016\/j.asoc.2026.115445_bib0075","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.neucom.2021.08.063","article-title":"Cost-effective batch-mode multi-label active learning","volume":"463","author":"Gui","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2026.115445_bib0080","series-title":"2023 IEEE International Conference on Image Processing (ICIP)","first-page":"410","article-title":"Cost-efficient multi-instance multi-label active learning via correlation of features","author":"Su","year":"2023"},{"key":"10.1016\/j.asoc.2026.115445_bib0085","series-title":"2024 8th International Conference on Robotics, Control and Automation (ICRCA)","first-page":"453","article-title":"Active learning method based on pseudo-labeling","author":"Hou","year":"2024"},{"key":"10.1016\/j.asoc.2026.115445_bib0090","doi-asserted-by":"crossref","first-page":"3428","DOI":"10.1109\/TMI.2025.3565000","article-title":"Co-pseudo labeling and active selection for fundus single-positive multi-label learning","volume":"44","author":"Hu","year":"2025","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.asoc.2026.115445_bib0095","series-title":"Active Learning Literature Survey","author":"Settles","year":"2009"},{"key":"10.1016\/j.asoc.2026.115445_bib0100","series-title":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"998","article-title":"Learning class-conditional GANs with active sampling","author":"Xie","year":"2019"},{"issue":"2","key":"10.1016\/j.asoc.2026.115445_bib0105","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1007\/s10994-019-05855-6","article-title":"A survey on semi-supervised learning","volume":"109","author":"Van Engelen","year":"2020","journal-title":"Mach. Learn."},{"issue":"9","key":"10.1016\/j.asoc.2026.115445_bib0110","doi-asserted-by":"crossref","first-page":"8934","DOI":"10.1109\/TKDE.2022.3220219","article-title":"A survey on deep semi-supervised learning","volume":"35","author":"Yang","year":"2022","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"1","key":"10.1016\/j.asoc.2026.115445_bib0115","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/JPROC.2020.3004555","article-title":"A comprehensive survey on transfer learning","volume":"109","author":"Zhuang","year":"2020","journal-title":"Proc. IEEE"},{"issue":"3","key":"10.1016\/j.asoc.2026.115445_bib0120","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3386252","article-title":"Generalizing from a few examples: a survey on few-shot learning","volume":"53","author":"Wang","year":"2020","journal-title":"ACM computing surveys (csur)"},{"issue":"9","key":"10.1016\/j.asoc.2026.115445_bib0125","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3472291","article-title":"A survey of deep active learning","volume":"54","author":"Ren","year":"2021","journal-title":"ACM computing surveys (CSUR)"},{"key":"10.1016\/j.asoc.2026.115445_bib0130","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.ins.2022.07.182","article-title":"Stable matching-based two-way selection in multi-label active learning with imbalanced data","volume":"610","author":"Chen","year":"2022","journal-title":"Inf. Sci."},{"key":"10.1016\/j.asoc.2026.115445_bib0135","series-title":"Advances in Neural Information Processing Systems, 36","first-page":"9789","article-title":"Navigating the pitfalls of active learning evaluation: a systematic framework for meaningful performance assessment","author":"L\u00fcth","year":"2023"},{"key":"10.1016\/j.asoc.2026.115445_bib0140","first-page":"596","article-title":"Fixmatch: simplifying semi-supervised learning with consistency and confidence","volume":"33","author":"Sohn","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"7","key":"10.1016\/j.asoc.2026.115445_bib0145","first-page":"3676","article-title":"Partial multi-label learning with noisy label identification","volume":"44","author":"Xie","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"10.1016\/j.asoc.2026.115445_bib0150","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1109\/TPAMI.2022.3141240","article-title":"CCMN: a general framework for learning with class-conditional multi-label noise","volume":"45","author":"Xie","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"11","key":"10.1016\/j.asoc.2026.115445_bib0155","doi-asserted-by":"crossref","first-page":"5098","DOI":"10.1109\/TKDE.2021.3054465","article-title":"A novel probabilistic label enhancement algorithm for multi-label distribution learning","volume":"34","author":"Tan","year":"2021","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.asoc.2026.115445_bib0160","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"14461","article-title":"Dist-pu: positive-unlabeled learning from a label distribution perspective","author":"Zhao","year":"2022"},{"issue":"5","key":"10.1016\/j.asoc.2026.115445_bib0165","doi-asserted-by":"crossref","first-page":"5970","DOI":"10.1109\/TPAMI.2022.3208419","article-title":"Maxmatch: semi-supervised learning with worst-case consistency","volume":"45","author":"Jiang","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.asoc.2026.115445_bib0170","series-title":"ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"1186","article-title":"Fine-grained engine fault sound event detection using multimodal signals","author":"Fedorishin","year":"2024"},{"key":"10.1016\/j.asoc.2026.115445_bib0175","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence, 38","first-page":"13754","article-title":"DC-NAS: divide-and-conquer neural architecture search for multi-modal classification","author":"Liang","year":"2024"},{"key":"10.1016\/j.asoc.2026.115445_bib0180","series-title":"2018 IEEE International Conference on Data Mining (ICDM)","first-page":"905","article-title":"Cost effective multi-label active learning via querying subexamples","author":"Chen","year":"2018"},{"key":"10.1016\/j.asoc.2026.115445_bib0185","series-title":"Workshop on Challenges in Representation Learning, ICML, 3","first-page":"896","article-title":"Pseudo-label: the simple and efficient semi-supervised learning method for deep neural networks","author":"Lee","year":"2013"},{"key":"10.1016\/j.asoc.2026.115445_bib0190","series-title":"Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"534","article-title":"Rank-loss support instance machines for MIML instance annotation","author":"Briggs","year":"2012"},{"key":"10.1016\/j.asoc.2026.115445_bib0195","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1016\/j.neucom.2017.08.001","article-title":"Effective active learning strategy for multi-label learning","volume":"273","author":"Reyes","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2026.115445_bib0200","first-page":"892","article-title":"Active learning by querying informative and representative examples","volume":"23","author":"Huang","year":"2010","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"5","key":"10.1016\/j.asoc.2026.115445_bib0205","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1109\/TNNLS.2018.2869164","article-title":"Bag-level aggregation for multiple-instance active learning in instance classification problems","volume":"30","author":"Carbonneau","year":"2018","journal-title":"IEEE Trans. on neural networks and learning systems"},{"key":"10.1016\/j.asoc.2026.115445_bib0210","series-title":"Analysis of Large and Complex Data","first-page":"91","article-title":"Active multi-instance multi-label learning","author":"Retz","year":"2016"},{"issue":"3","key":"10.1016\/j.asoc.2026.115445_bib0215","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: a library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM transactions on intelligent systems and technology (TIST)"},{"key":"10.1016\/j.asoc.2026.115445_bib0220","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence, 33","first-page":"4400","article-title":"Ranking-based deep cross-modal hashing","author":"Liu","year":"2019"},{"key":"10.1016\/j.asoc.2026.115445_bib0225","series-title":"2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)","first-page":"517","article-title":"Multi-label emotion classification in music videos using ensembles of audio and video features","author":"Kostiuk","year":"2019"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626008938?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626008938?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T07:51:38Z","timestamp":1783669898000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626008938"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":45,"alternative-id":["S1568494626008938"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115445","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Multi-stage cost-efficient multi-label active learning","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115445","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115445"}}