{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T01:49:40Z","timestamp":1766108980449,"version":"3.48.0"},"reference-count":54,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61503038"],"award-info":[{"award-number":["61503038"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61403042"],"award-info":[{"award-number":["61403042"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Education Department of Liaoning Province","award":["LQ2020013"],"award-info":[{"award-number":["LQ2020013"]}]},{"name":"Education Department of Liaoning Province","award":["LJKMZ20221484"],"award-info":[{"award-number":["LJKMZ20221484"]}]},{"name":"Application Basic Research Plan of Liaoning Province","award":["2022JH2\/101300282"],"award-info":[{"award-number":["2022JH2\/101300282"]}]},{"DOI":"10.13039\/501100005047","name":"Liaoning Natural Science Foundation","doi-asserted-by":"crossref","award":["2023-MS-294"],"award-info":[{"award-number":["2023-MS-294"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2026,3,15]]},"abstract":"<jats:p>Industrial products anomaly detection plays an important role in intelligent manufacturing process. Unsupervised anomaly detection has been widely popular in recent years, but only using normal samples to train the model will lead to over-generalization of the model. Based on this, a novel anomaly detection algorithm with adaptive complementary channels and complete span enhancement (ACCE) is proposed. Based on the differences in product defect rates, the ACCE system constructed a three-level structural anomaly model and a diversified logical anomaly model for data enhancement, thereby significantly improving the matching degree between generated anomalies and real anomalies. Meanwhile, in order to fully explore the potential value of generating abnormal data, ACCE proposed a teacher\u2013student collaborative training framework with maximum diffusion loss, strengthened the discrimination boundary of abnormal features, and achieved more accurate segmentation performance. Furthermore, a secondary de-differentiation adaptive complementary channel selection module was designed on the student network, integrating frequency domain de-differentiation, local-global cascade LSTM (LGC-LSTM), and the adaptive channel weighting mechanism, effectively enhancing the network\u2019s ability to repair defect locations. Additionally, through the dual optimization of the fusion mechanism and attention fine-tuning, the teacher network has a stronger feature adaptability in the anomaly detection task. A large number of experiments on three mainstream datasets MVTec AD, MVTec 3D-AD and VisA demonstrate the validity and generalization ability of the proposed method. In addition, a real-world application of PCB board inspection validates the practicality of the model.<\/jats:p>","DOI":"10.1142\/s021812662550450x","type":"journal-article","created":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T03:57:03Z","timestamp":1755143823000},"source":"Crossref","is-referenced-by-count":0,"title":["Unsupervised Industrial Products Anomaly Detection Via Adaptive Complementary Channels and Complete Span Enhancement"],"prefix":"10.1142","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5008-2935","authenticated-orcid":false,"given":"Long","family":"Li","sequence":"first","affiliation":[{"name":"College of Control Science and Engineering, Bohai University, No. 19 Keji Road, Jinzhou 121013, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7724-6792","authenticated-orcid":false,"given":"Zhiyan","family":"Han","sequence":"additional","affiliation":[{"name":"College of Control Science and Engineering, Bohai University, No. 19 Keji Road, Jinzhou 121013, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4140-7355","authenticated-orcid":false,"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Control Science and Engineering, Bohai University, No. 19 Keji Road, Jinzhou 121013, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2025,9,15]]},"reference":[{"key":"S021812662550450XBIB001","doi-asserted-by":"publisher","DOI":"10.1145\/3439950"},{"key":"S021812662550450XBIB002","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2024.3441659"},{"key":"S021812662550450XBIB003","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.108860"},{"key":"S021812662550450XBIB004","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2021.3110743"},{"key":"S021812662550450XBIB005","doi-asserted-by":"publisher","DOI":"10.1142\/S0218126625501105"},{"key":"S021812662550450XBIB006","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.108512"},{"key":"S021812662550450XBIB007","first-page":"1","volume":"71","author":"Tao X.","year":"2022","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"S021812662550450XBIB008","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3199228"},{"key":"S021812662550450XBIB009","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3519543"},{"key":"S021812662550450XBIB010","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19821-2_27"},{"key":"S021812662550450XBIB011","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00954"},{"key":"S021812662550450XBIB012","first-page":"2579","volume":"9","author":"van der Maaten L.","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"S021812662550450XBIB013","doi-asserted-by":"publisher","DOI":"10.1142\/S0218126625501336"},{"key":"S021812662550450XBIB014","doi-asserted-by":"publisher","DOI":"10.1142\/S0218126623500500"},{"key":"S021812662550450XBIB015","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01466"},{"key":"S021812662550450XBIB016","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108846"},{"key":"S021812662550450XBIB017","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2024.02.001"},{"key":"S021812662550450XBIB018","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-024-05283-7"},{"key":"S021812662550450XBIB019","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00424"},{"key":"S021812662550450XBIB020","first-page":"2591","volume-title":"IEEE\/CVF Winter Conf. Applications of Computer Vision (WACV)","author":"Rudolph M.","year":"2022"},{"key":"S021812662550450XBIB021","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"S021812662550450XBIB022","doi-asserted-by":"crossref","unstructured":"T. Liu, B. Li, X. Du, B. Jiang, L. Geng, F. Wang and Z. Zhao, Fair: Frequency-aware image restoration for industrial visual anomaly detection, preprint (2023), arXiv:2309.07068.","DOI":"10.2139\/ssrn.4742821"},{"key":"S021812662550450XBIB023","doi-asserted-by":"publisher","DOI":"10.1142\/S0218126624502141"},{"key":"S021812662550450XBIB024","first-page":"802","volume-title":"Proc. 29th Int. Conf. Neural Information Processing Systems","author":"Shi X.","year":"2015"},{"key":"S021812662550450XBIB025","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178838"},{"key":"S021812662550450XBIB026","unstructured":"X. Zhang, C. Liu, D. Yang, T. Song, Y. Ye, K. Li and Y. Song, Rfaconv: Innovating spatial attention and standard convolutional operation, preprint (2024), arXiv:2304.03198."},{"key":"S021812662550450XBIB027","first-page":"9584","volume-title":"2019 IEEE\/CVF Conf. Computer Vision and Pattern Recognition (CVPR)","author":"Bergmann P.","year":"2019"},{"key":"S021812662550450XBIB028","doi-asserted-by":"publisher","DOI":"10.5220\/0010865000003124"},{"key":"S021812662550450XBIB029","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20056-4_23"},{"key":"S021812662550450XBIB030","unstructured":"D. P. Kingma and M. Welling, Auto-encoding variational bayes, preprint (2013), arXiv:1312.6114."},{"key":"S021812662550450XBIB031","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03905-6"},{"key":"S021812662550450XBIB032","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.11.018"},{"key":"S021812662550450XBIB033","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2024.3494772"},{"key":"S021812662550450XBIB034","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02348"},{"key":"S021812662550450XBIB035","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2023.3344383"},{"key":"S021812662550450XBIB036","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3293772"},{"key":"S021812662550450XBIB037","first-page":"8310","volume-title":"2021 IEEE\/CVF Int. Conf. Computer Vision (ICCV)","author":"Zavrtanik V.","year":"2021"},{"key":"S021812662550450XBIB038","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110508"},{"key":"S021812662550450XBIB039","unstructured":"G. Hinton, O. Vinyals and J. Dean, Distilling the knowledge in a neural network, preprint (2015), arXiv:1503.02531."},{"key":"S021812662550450XBIB040","first-page":"1","volume":"73","author":"He Y.","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"S021812662550450XBIB041","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00951"},{"key":"S021812662550450XBIB042","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110982"},{"key":"S021812662550450XBIB043","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00381"},{"key":"S021812662550450XBIB044","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2023.3241579"},{"key":"S021812662550450XBIB045","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"S021812662550450XBIB046","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"S021812662550450XBIB047","unstructured":"X. Li, Z. Huang, F. Xue and Y. Zhou, Musc: Zero-shot industrial anomaly classification and segmentation with mutual scoring of the unlabeled images, preprint (2024), arXiv:2401.16753."},{"key":"S021812662550450XBIB048","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i8.32856"},{"key":"S021812662550450XBIB049","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW59228.2023.00298"},{"key":"S021812662550450XBIB050","first-page":"6185","volume-title":"Proc. 40th Int. Conf. Machine Learning ICML 2023","author":"Chu Y.","year":"2023"},{"key":"S021812662550450XBIB051","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.127483"},{"key":"S021812662550450XBIB052","first-page":"75","volume-title":"Computer Vision \u2013 ECCV 2024","author":"Tu Y.","year":"2024"},{"key":"S021812662550450XBIB053","unstructured":"A. Mousakhan, T. Brox and J. Tayyub, Anomaly detection with conditioned denoising diffusion models, preprint (2023), arXiv:2305.15956."},{"key":"S021812662550450XBIB054","first-page":"37","volume-title":"Computer Vision \u2013 ECCV 2024","author":"Chen Q.","year":"2024"}],"container-title":["Journal of Circuits, Systems and Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S021812662550450X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T01:45:55Z","timestamp":1766108755000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S021812662550450X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,15]]},"references-count":54,"journal-issue":{"issue":"05","published-print":{"date-parts":[[2026,3,15]]}},"alternative-id":["10.1142\/S021812662550450X"],"URL":"https:\/\/doi.org\/10.1142\/s021812662550450x","relation":{},"ISSN":["0218-1266","1793-6454"],"issn-type":[{"type":"print","value":"0218-1266"},{"type":"electronic","value":"1793-6454"}],"subject":[],"published":{"date-parts":[[2025,9,15]]},"article-number":"2550450"}}