{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:33:37Z","timestamp":1753875217237,"version":"3.41.2"},"reference-count":43,"publisher":"Informa UK Limited","issue":"1","license":[{"start":{"date-parts":[[2024,5,11]],"date-time":"2024-05-11T00:00:00Z","timestamp":1715385600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U22A20106"],"award-info":[{"award-number":["U22A20106"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Foshan Science and technology innovation special foundation","award":["BK22BF001"],"award-info":[{"award-number":["BK22BF001"]}]},{"name":"Foshan Higher Education Advanced Talents Foundation","award":["BKBS202203"],"award-info":[{"award-number":["BKBS202203"]}]}],"content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["Applied Artificial Intelligence"],"published-print":{"date-parts":[[2024,12,31]]},"DOI":"10.1080\/08839514.2024.2349410","type":"journal-article","created":{"date-parts":[[2024,5,12]],"date-time":"2024-05-12T04:58:48Z","timestamp":1715489928000},"update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":0,"title":["A Human-In-One-Loop Active Domain Adaptation Framework for Digit Recognition"],"prefix":"10.1080","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8193-9834","authenticated-orcid":false,"given":"Hao","family":"Xiu","sequence":"first","affiliation":[{"name":"University of Science and Technology, Beijing, P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanchen","family":"Li","sequence":"additional","affiliation":[{"name":"University of Science and Technology, Beijing, P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"He","sequence":"additional","affiliation":[{"name":"University of Science and Technology, Beijing, P.R. China"},{"name":"Liaoning Academy of Materials, Shenyang, Liaoning, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaotong","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Science and Technology, Beijing, P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Qi","sequence":"additional","affiliation":[{"name":"University of Science and Technology, Beijing, P.R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"301","published-online":{"date-parts":[[2024,5,11]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09545-7"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btl242"},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.18"},{"key":"e_1_3_3_5_1","volume-title":"Advances in Neural Information Processing Systems","volume":"29","author":"Bousmalis K.","year":"2016","unstructured":"Bousmalis, K., G. Trigeorgis, N. Silberman, D. Krishnan, and D. Erhan. 2016. Domain separation networks, Advances in Neural Information Processing Systems, Barcelona, Spain, 29."},{"key":"e_1_3_3_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102062"},{"key":"e_1_3_3_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2021.1912711"},{"key":"e_1_3_3_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110409"},{"key":"e_1_3_3_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-012-0507-8"},{"issue":"1","key":"e_1_3_3_10_1","first-page":"2096","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"Ganin Y.","year":"2016","unstructured":"Ganin, Y., E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, and V. Lempitsky. 2016. Domain-adversarial training of neural networks. The Journal of Machine Learning Research 17 (1):2096\u20132030.","journal-title":"The Journal of Machine Learning Research"},{"key":"e_1_3_3_11_1","article-title":"Domain adaptation via prompt learning","author":"Ge C.","year":"2023","unstructured":"Ge, C., R. Huang, M. Xie, Z. Lai, S. Song, S. Li, and G. Huang. 2023. Domain adaptation via prompt learning. IEEE Transactions on Neural Networks and Learning Systems.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"e_1_3_3_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.293"},{"key":"e_1_3_3_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_36"},{"key":"e_1_3_3_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2023.101048"},{"key":"e_1_3_3_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"e_1_3_3_16_1","first-page":"30","volume-title":"Advances in Neural Information Processing Systems","author":"Kendall A.","year":"2017","unstructured":"Kendall, A., and Y. Gal. 2017. What uncertainties do we need in bayesian deep learning for computer vision?. Advances in Neural Information Processing Systems, Long Beach, California, USA, 30."},{"key":"e_1_3_3_17_1","first-page":"30","volume-title":"Advances in Neural Information Processing Systems","author":"Konyushkova K.","year":"2017","unstructured":"Konyushkova, K., R. Sznitman, and P. Fua. 2017. Learning active learning from data, Advances in Neural Information Processing Systems, Long Beach, California, USA, 30."},{"key":"e_1_3_3_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.110023"},{"key":"e_1_3_3_19_1","first-page":"2208","volume-title":"International Conference on Machine Learning","author":"Long M.","year":"2017","unstructured":"Long, M., H. Zhu, J. Wang, and M. I. Jordan. 2017. Deep transfer learning with joint adaptation networks. International Conference on Machine Learning, Sydney, Australia, 2208\u201317."},{"key":"e_1_3_3_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.06.008"},{"key":"e_1_3_3_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00884"},{"key":"e_1_3_3_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093556"},{"key":"e_1_3_3_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00839"},{"key":"e_1_3_3_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00742"},{"key":"e_1_3_3_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3472291"},{"key":"e_1_3_3_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00814"},{"key":"e_1_3_3_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"e_1_3_3_28_1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan K.","year":"2014","unstructured":"Simonyan, K., and A. Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv Preprint arXiv: 14091556.","journal-title":"arXiv Preprint arXiv: 14091556"},{"key":"e_1_3_3_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093390"},{"key":"e_1_3_3_30_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2023.2195596"},{"key":"e_1_3_3_31_1","article-title":"Deep domain confusion: Maximizing for domain invariance","author":"Tzeng E.","year":"2014","unstructured":"Tzeng, E., J. Hoffman, N. Zhang, K. Saenko, and T. Darrell. 2014. Deep domain confusion: Maximizing for domain invariance. arXiv Preprint arXiv: 14123474.","journal-title":"arXiv Preprint arXiv: 14123474"},{"key":"e_1_3_3_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.083"},{"key":"e_1_3_3_33_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015345"},{"key":"e_1_3_3_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580815"},{"key":"e_1_3_3_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2022.05.017"},{"key":"e_1_3_3_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2022.05.014"},{"key":"e_1_3_3_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3197930"},{"key":"e_1_3_3_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.107"},{"key":"e_1_3_3_39_1","first-page":"27","volume-title":"Advances in Neural Information Processing Systems","author":"Yosinski J.","year":"2014","unstructured":"Yosinski, J., J. Clune, Y. Bengio, and H. Lipson. 2014. How transferable are features in deep neural networks?, Advances in Neural Information Processing Systems, Montreal, Quebec, Canada, 27."},{"key":"e_1_3_3_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03467-7"},{"key":"e_1_3_3_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207365"},{"key":"e_1_3_3_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3028503"},{"key":"e_1_3_3_43_1","article-title":"Semi-supervised anomaly detection via neural process","author":"Zhou F.","year":"2023","unstructured":"Zhou, F., G. Wang, K. Zhang, S. Liu, and T. Zhong. 2023. Semi-supervised anomaly detection via neural process, IEEE Transactions on Knowledge and Data Engineering.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_3_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["Applied Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/08839514.2024.2349410","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T16:18:28Z","timestamp":1734365908000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/08839514.2024.2349410"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,11]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,12,31]]}},"alternative-id":["10.1080\/08839514.2024.2349410"],"URL":"https:\/\/doi.org\/10.1080\/08839514.2024.2349410","relation":{},"ISSN":["0883-9514","1087-6545"],"issn-type":[{"type":"print","value":"0883-9514"},{"type":"electronic","value":"1087-6545"}],"subject":[],"published":{"date-parts":[[2024,5,11]]},"assertion":[{"value":"The publishing and review policy for this title is described in its Aims & Scope.","order":1,"name":"peerreview_statement","label":"Peer Review Statement"},{"value":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=uaai20","URL":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=uaai20","order":2,"name":"aims_and_scope_url","label":"Aim & Scope"},{"value":"2023-03-26","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-04-11","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-04-18","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-05-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2349410"}}