{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T02:03:21Z","timestamp":1782525801767,"version":"3.54.5"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72271034"],"award-info":[{"award-number":["72271034"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1007\/s10489-024-05423-z","type":"journal-article","created":{"date-parts":[[2024,4,9]],"date-time":"2024-04-09T10:02:03Z","timestamp":1712656923000},"page":"4878-4889","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Domain generalization based on domain-specific adversarial learning"],"prefix":"10.1007","volume":"54","author":[{"given":"Ziping","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5315-8712","authenticated-orcid":false,"given":"Xiaohang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengren","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,9]]},"reference":[{"key":"5423_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103757","volume":"120","author":"K Ayodele","year":"2020","unstructured":"Ayodele K, Ikezogwo W, Komolafe M, Ogunbona P (2020) Supervised domain generalization for integration of disparate scalp eeg datasets for automatic epileptic seizure detection. Computers in Biology and Medicine 120:103757","journal-title":"Computers in Biology and Medicine"},{"key":"5423_CR2","doi-asserted-by":"crossref","unstructured":"Carlucci FM, D\u2019Innocente A, Bucci S, Caputo B, Tommasi T (2019) Domain generalization by solving jigsaw puzzles. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 2229\u20132238","DOI":"10.1109\/CVPR.2019.00233"},{"issue":"12","key":"5423_CR3","doi-asserted-by":"publisher","first-page":"4441","DOI":"10.1109\/TPAMI.2020.3001338","volume":"43","author":"FM Carlucci","year":"2021","unstructured":"Carlucci FM, Porzi L, Caputo B, Ricci E, Bul\u00f3 SR (2021) Multidial: Domain alignment layers for (multisource) unsupervised domain adaptation. IEEE Transactions on pattern analysis and machine intelligence 43(12):4441\u20134452","journal-title":"IEEE Transactions on pattern analysis and machine intelligence"},{"key":"5423_CR4","doi-asserted-by":"crossref","unstructured":"Chattopadhyay P, Balaji Y, Hoffman J (2020) Learning to balance specificity and invariance for in and out of domain generalization. In: European conference on computer vision, Springer, pp 301\u2013318","DOI":"10.1007\/978-3-030-58545-7_18"},{"key":"5423_CR5","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1016\/j.neucom.2021.09.046","volume":"467","author":"K Chen","year":"2022","unstructured":"Chen K, Zhuang D, Chang JM (2022) Discriminative adversarial domain generalization with meta-learning based cross-domain validation. Neurocomputing 467:418\u2013426","journal-title":"Neurocomputing"},{"key":"5423_CR6","doi-asserted-by":"crossref","unstructured":"D\u2019Innocente A, Caputo B (2018) Domain generalization with domain-specific aggregation modules. In: German Conference on Pattern Recognition, Springer, pp 187\u2013198","DOI":"10.1007\/978-3-030-12939-2_14"},{"key":"5423_CR7","unstructured":"Donahue J, Jia Y, Vinyals O, Hoffman J, Darrell T (2014) Decaf: A deep convolutional activation feature for generic visual recognition. In: International conference on machine learning, PMLR, pp 647\u2013655"},{"key":"5423_CR8","unstructured":"Ganin Y, Lempitsky V (2015) Unsupervised domain adaptation by backpropagation. In: International conference on machine learning, PMLR, pp 1180\u20131189"},{"key":"5423_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2022.103503","volume":"222","author":"Z Ge","year":"2022","unstructured":"Ge Z, Song Z, Li X, Zhang L (2022) Meta conditional variational auto-encoder for domain generalization. Computer Vision and Image Understanding 222:103503","journal-title":"Computer Vision and Image Understanding"},{"key":"5423_CR10","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. Adv Neural Inform Process Syst 27"},{"key":"5423_CR11","doi-asserted-by":"crossref","unstructured":"Huang Z, Wang H, Xing EP, Huang D (2020) Self-challenging improves cross-domain generalization. In: Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, Proceedings, Part II 16, Springer, pp 124\u2013140. Accessed 23\u201328 Aug 2020","DOI":"10.1007\/978-3-030-58536-5_8"},{"key":"5423_CR12","doi-asserted-by":"crossref","unstructured":"Jin X, Lan C, Zeng W, Chen Z, Zhang L (2020) Style normalization and restitution for generalizable person re-identification. In: 2020 IEEE\/CVF Conference on computer vision and pattern recognition (CVPR), pp 3140\u20133149","DOI":"10.1109\/CVPR42600.2020.00321"},{"key":"5423_CR13","doi-asserted-by":"publisher","first-page":"3636","DOI":"10.1109\/TMM.2021.3104379","volume":"24","author":"X Jin","year":"2022","unstructured":"Jin X, Lan C, Zeng W, Chen Z (2022) Style normalization and restitution for domain generalization and adaptation. IEEE Transactions on Multimedia 24:3636\u20133651","journal-title":"IEEE Transactions on Multimedia"},{"key":"5423_CR14","doi-asserted-by":"crossref","unstructured":"Kang G, Lu J, Yi Y, Hauptmann AG (2019) Contrastive adaptation network for unsupervised domain adaptation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 4893\u20134902","DOI":"10.1109\/CVPR.2019.00503"},{"key":"5423_CR15","unstructured":"Krueger D, Caballero E, Jacobsen JH, Zhang A, Binas J, Zhang D, Priol RL, Courville A (2021) Out-of-distribution generalization via risk extrapolation (rex). In: International conference on machine learning"},{"key":"5423_CR16","doi-asserted-by":"crossref","unstructured":"Li D, Yang Y, Song YZ, Hospedales TM (2017) Deeper, broader and artier domain generalization. In: Proceedings of the IEEE international conference on computer vision, pp 5542\u20135550","DOI":"10.1109\/ICCV.2017.591"},{"key":"5423_CR17","doi-asserted-by":"crossref","unstructured":"Li H, Pan SJ, Wang S, Kot AC (2018) Domain generalization with adversarial feature learning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5400\u20135409","DOI":"10.1109\/CVPR.2018.00566"},{"key":"5423_CR18","doi-asserted-by":"crossref","unstructured":"Li P, Li D, Li W, Gong S, Fu Y, Hospedales TM (2021) A simple feature augmentation for domain generalization. In: 2021 IEEE\/CVF International conference on computer vision (ICCV), pp 8866\u20138875","DOI":"10.1109\/ICCV48922.2021.00876"},{"key":"5423_CR19","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1016\/j.neucom.2020.05.014","volume":"403","author":"X Li","year":"2020","unstructured":"Li X, Zhang W, Ma H, Luo Z, Li X (2020) Domain generalization in rotating machinery fault diagnostics using deep neural networks. Neurocomputing 403:409\u2013420","journal-title":"Neurocomputing"},{"issue":"3","key":"5423_CR20","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1109\/TETCI.2021.3115666","volume":"6","author":"X Li","year":"2022","unstructured":"Li X, Zhang Z, Gao L, Wen L (2022) A new semi-supervised fault diagnosis method via deep coral and transfer component analysis. IEEE Transactions on emerging topics in computational intelligence 6(3):690\u2013699","journal-title":"IEEE Transactions on emerging topics in computational intelligence"},{"key":"5423_CR21","doi-asserted-by":"crossref","unstructured":"Li Y, Gong M, Tian X, Liu T, Tao D (2018) Deep domain generalization via conditional invariant adversarial networks. In: Proceedings of the European conference on computer vision (ECCV), pp 624\u2013639","DOI":"10.1007\/978-3-030-01267-0_38"},{"key":"5423_CR22","unstructured":"Li Y, Yang Y, Zhou W, Hospedales TM (2019) Feature-critic networks for heterogeneous domain generalization. In: International conference on machine learning, PMLR, pp 3915\u20133924"},{"key":"5423_CR23","doi-asserted-by":"crossref","unstructured":"Li Y, Hu W, Li H, Dong H, Zhang B, Tian Q (2020) Aligning discriminative and representative features: An unsupervised domain adaptation method for building damage assessment. IEEE Transactions on image processing 29:6110\u20136122","DOI":"10.1109\/TIP.2020.2988175"},{"issue":"1","key":"5423_CR24","doi-asserted-by":"publisher","first-page":"1062","DOI":"10.1109\/TNNLS.2022.3179805","volume":"35","author":"ZG Liu","year":"2024","unstructured":"Liu ZG, Ning LB, Zhang ZW (2024) A new progressive multisource domain adaptation network with weighted decision fusion. IEEE Transactions on neural networks and learning systems 35(1):1062\u20131072","journal-title":"IEEE Transactions on neural networks and learning systems"},{"key":"5423_CR25","doi-asserted-by":"publisher","first-page":"11749","DOI":"10.1609\/aaai.v34i07.6846","volume":"34","author":"T Matsuura","year":"2020","unstructured":"Matsuura T, Harada T (2020) Domain generalization using a mixture of multiple latent domains. Proceedings of the AAAI conference on artificial intelligence 34:11749\u201311756","journal-title":"Proceedings of the AAAI conference on artificial intelligence"},{"key":"5423_CR26","doi-asserted-by":"crossref","unstructured":"Nam H, Lee H, Park J, Yoon W, Yoo D (2021) Reducing domain gap by reducing style bias. In: 2021 IEEE\/CVF Conference on computer vision and pattern recognition (CVPR), pp 8686\u20138695","DOI":"10.1109\/CVPR46437.2021.00858"},{"key":"5423_CR27","unstructured":"Parascandolo G, Neitz A, Orvieto A, Gresele L, Schlkopf B (2021) Learning explanations that are hard to vary. In: International conference on learning representations"},{"key":"5423_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107124","volume":"100","author":"MM Rahman","year":"2020","unstructured":"Rahman MM, Fookes C, Baktashmotlagh M, Sridharan S (2020) Correlation-aware adversarial domain adaptation and generalization. Pattern Recog 100:107124","journal-title":"Pattern Recog"},{"issue":"5","key":"5423_CR29","doi-asserted-by":"publisher","first-page":"1989","DOI":"10.1109\/TNNLS.2020.2995648","volume":"32","author":"CX Ren","year":"2021","unstructured":"Ren CX, Ge P, Yang P, Yan S (2021) Learning target-domain-specific classifier for partial domain adaptation. IEEE Transactions on neural networks and learning systems 32(5):1989\u20132001","journal-title":"IEEE Transactions on neural networks and learning systems"},{"key":"5423_CR30","doi-asserted-by":"crossref","unstructured":"Sicilia A, Zhao X, Hwang SJ (2023) Domain adversarial neural networks for domain generalization: when it works and how to improve. Mach Learn 112:26856\u20132721","DOI":"10.1007\/s10994-023-06324-x"},{"key":"5423_CR31","doi-asserted-by":"crossref","unstructured":"Venkateswara H, Eusebio J, Chakraborty S, Panchanathan S (2017) Deep hashing network for unsupervised domain adaptation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5018\u20135027","DOI":"10.1109\/CVPR.2017.572"},{"key":"5423_CR32","doi-asserted-by":"crossref","unstructured":"Xu R, Chen Z, Zuo W, Yan J, Liang L (2018) Deep cocktail network: Multi-source unsupervised domain adaptation with category shift. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3964\u20133973","DOI":"10.1109\/CVPR.2018.00417"},{"issue":"12","key":"5423_CR33","doi-asserted-by":"publisher","first-page":"7957","DOI":"10.1109\/TII.2021.3064377","volume":"17","author":"W Zhang","year":"2021","unstructured":"Zhang W, Li X, Ma H, Luo Z, Li X (2021) Universal domain adaptation in fault diagnostics with hybrid weighted deep adversarial learning. IEEE Transactions on industrial informatics 17(12):7957\u20137967","journal-title":"IEEE Transactions on industrial informatics"},{"key":"5423_CR34","first-page":"16096","volume":"33","author":"S Zhao","year":"2020","unstructured":"Zhao S, Gong M, Liu T, Fu H, Tao D (2020) Domain generalization via entropy regularization. Adv Neural Inform Process Syst 33:16096\u201316107","journal-title":"Adv Neural Inform Process Syst"},{"key":"5423_CR35","doi-asserted-by":"crossref","unstructured":"Zhao S, Yu Z, Marbach TG, Wang G, Yin A, Zhou Y, Liu X (2023) Mdgad: Meta domain generalization for distribution drift in anomaly detection. Neurocomputing 550:126483","DOI":"10.1016\/j.neucom.2023.126483"},{"key":"5423_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2021.3126847","volume":"70","author":"H Zheng","year":"2021","unstructured":"Zheng H, Yang Y, Yin J, Li Y, Wang R, Xu M (2021) Deep domain generalization combining a priori diagnosis knowledge toward cross-domain fault diagnosis of rolling bearing. IEEE Transactions on instrumentation and measurement 70:1\u201311","journal-title":"IEEE Transactions on instrumentation and measurement"},{"key":"5423_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.127114","volume":"569","author":"T Zheng","year":"2024","unstructured":"Zheng T, Chen Z, Ding S, Cai C, Luo J (2024) Adv-4-adv: Thwarting changing adversarial perturbations via adversarial domain adaptation. Neurocomputing 569:127114","journal-title":"Neurocomputing"},{"key":"5423_CR38","doi-asserted-by":"publisher","first-page":"5989","DOI":"10.1609\/aaai.v33i01.33015989","volume":"33","author":"Y Zhu","year":"2019","unstructured":"Zhu Y, Zhuang F, Wang D (2019) Aligning domain-specific distribution and classifier for cross-domain classification from multiple sources. Proceedings of the AAAI conference on artificial intelligence 33:5989\u20135996","journal-title":"Proceedings of the AAAI conference on artificial intelligence"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05423-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-05423-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05423-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T13:07:53Z","timestamp":1714396073000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-05423-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3]]},"references-count":38,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["5423"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-05423-z","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3]]},"assertion":[{"value":"27 March 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}