{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:52:48Z","timestamp":1772823168176,"version":"3.50.1"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003995","name":"Natural Science Foundation of Anhui Province","doi-asserted-by":"publisher","award":["2308085MF219"],"award-info":[{"award-number":["2308085MF219"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1109\/jbhi.2024.3375889","type":"journal-article","created":{"date-parts":[[2024,3,18]],"date-time":"2024-03-18T19:19:05Z","timestamp":1710789545000},"page":"3501-3512","source":"Crossref","is-referenced-by-count":15,"title":["SCAC: A Semi-Supervised Learning Approach for Cervical Abnormal Cell Detection"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-2664-9139","authenticated-orcid":false,"given":"Zheng","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Precision Machinery and Precision Instrument, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0717-2836","authenticated-orcid":false,"given":"Peng","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Microelectronics, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6358-767X","authenticated-orcid":false,"given":"Mingxiao","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Precision Machinery and Precision Instrument, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4755-775X","authenticated-orcid":false,"given":"Liang","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Pathology, Guangzhou Women and Children&#x0027;s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1249-1786","authenticated-orcid":false,"given":"Pengfei","family":"Shao","sequence":"additional","affiliation":[{"name":"Department of Precision Machinery and Precision Instrument, University of Science and Technology of China, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6083-1442","authenticated-orcid":false,"given":"Shuwei","family":"Shen","sequence":"additional","affiliation":[{"name":"Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2486-5677","authenticated-orcid":false,"given":"Ronald X.","family":"Xu","sequence":"additional","affiliation":[{"name":"Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2994778"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/bjc.2016.290"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10552-012-0011-1"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1159\/000477556"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jasc.2019.03.003"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2016.2519686"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3276919"},{"key":"ref9","first-page":"52","article-title":"Detection and classification of cervical exfoliated cells based on faster R-CNN","volume-title":"Proc. IEEE 11th Int. Conf. Adv. Infocomm Technol.","author":"Li"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-60639-8_50"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00644"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-23913-3"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-25296-x"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3163171"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.01.006"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI52829.2022.9761652"},{"key":"ref17","first-page":"596","article-title":"Fixmatch: Simplifying semi-supervised learning with consistency and confidence","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sohn"},{"key":"ref18","article-title":"Selfmatch: Combining contrastive self-supervision and consistency for semi-supervised learning","author":"Kim","year":"2021"},{"key":"ref19","first-page":"18408","article-title":"Flexmatch: Boosting semi-supervised learning with curriculum pseudo labeling","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00020"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20077-9_3"},{"key":"ref23","first-page":"25956","article-title":"Openmatch: Open-set semi-supervised learning with open-set consistency regularization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Saito"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00305"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.l007\/978-3-319-46448-0_2"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00972"},{"key":"ref28","first-page":"1","article-title":"Faster r-cnn: Towards real-time object detection with region proposal networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ren"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00975"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00298"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00913"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00720"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3118953"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01509"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.3390\/rs14153829"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbe.2020.01.016"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106061"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32692-0_8"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102197"},{"key":"ref44","article-title":"A simple semi-supervised learning framework for object detection","author":"Sohn","year":"2020"},{"key":"ref45","article-title":"Freematch: Self-adaptive thresholding for semi-supervised learning","author":"Wang","year":"2022"},{"key":"ref46","article-title":"Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring","author":"Berthelot","year":"2019"},{"key":"ref47","article-title":"Unbiased teacher for semi-supervised object detection","author":"Liu","year":"2021"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20077-9_27"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00315"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102117"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00373"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00218"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2995518"},{"key":"ref54","first-page":"6256","article-title":"Unsupervised data augmentation for consistency training","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Xie"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00477"},{"key":"ref56","first-page":"1","article-title":"Mixmatch: A holistic approach to semi-supervised learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Berthelot"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref58","article-title":"Mixup: Beyond empirical risk minimization","author":"Zhang","year":"2017"},{"key":"ref59","article-title":"Improved regularization of convolutional neural networks with cutout","author":"DeVries","year":"2017"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref61","article-title":"MMDetection: Open mmlab detection toolbox and benchmark","author":"Chen","year":"2019"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref64","article-title":"High-resolution representations for labeling pixels and regions","author":"Sun","year":"2019"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00408"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01422"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00316"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12102477"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/10550931\/10468580.pdf?arnumber=10468580","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T20:07:38Z","timestamp":1736971658000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10468580\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6]]},"references-count":68,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2024.3375889","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6]]}}}