{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:59:30Z","timestamp":1760597970149,"version":"3.37.3"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T00:00:00Z","timestamp":1595980800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T00:00:00Z","timestamp":1595980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s11760-020-01745-w","type":"journal-article","created":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T17:02:46Z","timestamp":1596042166000},"page":"279-287","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Joint distinct subspace learning and unsupervised transfer classification for visual domain adaptation"],"prefix":"10.1007","volume":"15","author":[{"given":"Shiva","family":"Noori\u00a0Saray","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4893-1272","authenticated-orcid":false,"given":"Jafar","family":"Tahmoresnezhad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,7,29]]},"reference":[{"key":"1745_CR1","unstructured":"Csurka, G.: Domain adaptation for visual applications: a comprehensive survey (2017). arXiv preprint arXiv:1702.05374"},{"key":"1745_CR2","doi-asserted-by":"crossref","unstructured":"Tahmoresnezhad, J., Hashemi, S.: Common feature extraction in multi-source domains for transfer learning. In: 2015 7th Conference on Information and Knowledge Technology (IKT), pp. 1\u20135 (2015)","DOI":"10.1109\/IKT.2015.7288795"},{"key":"1745_CR3","doi-asserted-by":"publisher","first-page":"292","DOI":"10.3906\/elk-1503-245","volume":"25","author":"J Tahmoresnezhad","year":"2017","unstructured":"Tahmoresnezhad, J., Hashemi, S.: Exploiting kernel-based feature weighting and instance clustering to transfer knowledge across domains. Turk. J. Electr. Eng. Comput. Sci. 25, 292\u2013307 (2017)","journal-title":"Turk. J. Electr. Eng. Comput. Sci."},{"key":"1745_CR4","doi-asserted-by":"crossref","unstructured":"Zhang, J., Li, W., Ogunbona, P.: Joint geometrical and statistical alignment for visual domain adaptation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1859\u20131867 (2017)","DOI":"10.1109\/CVPR.2017.547"},{"key":"1745_CR5","doi-asserted-by":"crossref","unstructured":"Azab, A.M., Toth, J., Mihaylova, L.S., Arvaneh, M.: A review on transfer learning approaches in brain\u2013computer interface. In: Signal Processing and Machine Learning for Brain\u2013Machine Interfaces, pp. 81\u2013101. Institution of Engineering and Technology (2018)","DOI":"10.1049\/PBCE114E_ch5"},{"key":"1745_CR6","unstructured":"Gong, B., Shi, Y., Sha, F., Grauman, K.: Geodesic flow kernel for unsupervised domain adaptation. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2066\u20132073 (2012)"},{"key":"1745_CR7","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86, 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"key":"1745_CR8","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1109\/34.291440","volume":"16","author":"JJ Hull","year":"1994","unstructured":"Hull, J.J.: A database for handwritten text recognition research. IEEE Trans. Pattern Anal. Mach. Intell. 16, 550\u2013554 (1994)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1745_CR9","doi-asserted-by":"crossref","unstructured":"Wang, J., Feng, W., Chen, Y., Yu, H., Huang, M., Yu, P.S.: Visual domain adaptation with manifold embedded distribution alignment. In: Proceedings of the 26th ACM International Conference on Multimedia, pp. 402\u2013410 (2018)","DOI":"10.1145\/3240508.3240512"},{"key":"1745_CR10","unstructured":"Sim, T., Baker, S., Bsat, M.: The CMU pose, illumination, and expression (PIE) database. In: Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition, pp. 53\u201358 (2002)"},{"key":"1745_CR11","unstructured":"Asgarian, A., et al.: A hybrid instance-based transfer learning method (2018). arXiv preprint arXiv:1812.01063"},{"key":"1745_CR12","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"K Weiss","year":"2016","unstructured":"Weiss, K., Khoshgoftaar, T.M., Wang, D.: A survey of transfer learning. J. Big Data 3, 9 (2016)","journal-title":"J. Big Data"},{"key":"1745_CR13","doi-asserted-by":"publisher","first-page":"1414","DOI":"10.1109\/TPAMI.2016.2599532","volume":"39","author":"M Ghifary","year":"2016","unstructured":"Ghifary, M., Balduzzi, D., Kleijn, W.B., Zhang, M.: Scatter component analysis: a unified framework for domain adaptation and domain generalization. IEEE Trans. Pattern Anal. Mach. Intell. 39, 1414\u20131430 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1745_CR14","doi-asserted-by":"crossref","unstructured":"Long, M., Wang, J., Ding, G., Sun, J., Yu, P.S.: Transfer feature learning with joint distribution adaptation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2200\u20132207 (2013)","DOI":"10.1109\/ICCV.2013.274"},{"key":"1745_CR15","doi-asserted-by":"crossref","unstructured":"Mahadevan, S., Mishra, B., Ghosh, S.: A unified framework for domain adaptation using metric learning on manifolds. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 843\u2013860. Springer (2018)","DOI":"10.1007\/978-3-030-10928-8_50"},{"key":"1745_CR16","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.ijmedinf.2018.01.001","volume":"112","author":"J Rubin","year":"2018","unstructured":"Rubin, J., et al.: An ensemble boosting model for predicting transfer to the pediatric intensive care unit. Int. J. Med. Inform. 112, 15\u201320 (2018)","journal-title":"Int. J. Med. Inform."},{"key":"1745_CR17","doi-asserted-by":"crossref","unstructured":"Ben-David, S., Blitzer, J., Crammer, K., Pereira, F.: Analysis of representations for domain adaptation. In: Advances in Neural Information Processing Systems, pp. 137\u2013144 (2007)","DOI":"10.7551\/mitpress\/7503.003.0022"},{"key":"1745_CR18","doi-asserted-by":"crossref","unstructured":"Wang, J., Chen, Y., Hao, S., Feng, W., Shen, Z.: Balanced distribution adaptation for transfer learning. In: 2017 IEEE International Conference on Data Mining (ICDM), pp. 1129\u20131134. IEEE (2017)","DOI":"10.1109\/ICDM.2017.150"},{"key":"1745_CR19","doi-asserted-by":"publisher","first-page":"1076","DOI":"10.1109\/TKDE.2013.111","volume":"26","author":"M Long","year":"2013","unstructured":"Long, M., Wang, J., Ding, G., Pan, S.J., Philip, S.Y.: Adaptation regularization: a general framework for transfer learning. IEEE Trans. Knowl. Data Eng. 26, 1076\u20131089 (2013)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"1745_CR20","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1109\/TIP.2015.2510498","volume":"25","author":"Y Xu","year":"2015","unstructured":"Xu, Y., Fang, X., Wu, J., Li, X., Zhang, D.: Discriminative transfer subspace learning via low-rank and sparse representation. IEEE Trans. Image Process. 25, 850\u2013863 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"1745_CR21","doi-asserted-by":"publisher","first-page":"4260","DOI":"10.1109\/TIP.2018.2839528","volume":"27","author":"S Li","year":"2018","unstructured":"Li, S., Song, S., Huang, G., Ding, Z., Wu, C.: Domain invariant and class discriminative feature learning for visual domain adaptation. IEEE Trans. Image Process. 27, 4260\u20134273 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"1745_CR22","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1007\/s10115-016-0944-x","volume":"50","author":"J Tahmoresnezhad","year":"2017","unstructured":"Tahmoresnezhad, J., Hashemi, S.: Visual domain adaptation via transfer feature learning. Knowl. Inf. Syst. 50, 585\u2013605 (2017)","journal-title":"Knowl. Inf. Syst."},{"key":"1745_CR23","doi-asserted-by":"crossref","unstructured":"Sun, B., Saenko, K.: Deep coral: correlation alignment for deep domain adaptation. In: European Conference on Computer Vision Workshops, pp. 443\u2013450 (2016)","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"1745_CR24","doi-asserted-by":"publisher","first-page":"804","DOI":"10.1049\/iet-ipr.2018.5871","volume":"13","author":"J Huang","year":"2019","unstructured":"Huang, J., Zhou, Z.: Transfer metric learning for unsupervised domain adaptation. IET Image Proc. 13, 804\u2013810 (2019)","journal-title":"IET Image Proc."},{"key":"1745_CR25","doi-asserted-by":"crossref","unstructured":"Tan, C., Sun, F., Kong, T., Zhang, W., Yang, C., Liu, C.: A survey on deep transfer learning. In: International Conference on Artificial Neural Networks, pp. 270\u2013279 (2018)","DOI":"10.1007\/978-3-030-01424-7_27"},{"key":"1745_CR26","doi-asserted-by":"crossref","unstructured":"Addabbo, P., Focareta, M., Marcuccio, S., Votto, C., Ullo, S.L.: Land cover classification and monitoring through multisensor image and data combination. In: 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 902\u2013905 (2016)","DOI":"10.1109\/IGARSS.2016.7729228"},{"key":"1745_CR27","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1109\/MAES.2018.170145","volume":"33","author":"P Addabbo","year":"2018","unstructured":"Addabbo, P., Angrisano, A., Bernardi, M.L., Gagliarde, G., Mennella, A., Nisi, M., Ullo, S.L.: UAV system for photovoltaic plant inspection. IEEE Aerosp. Electron. Syst. Mag. 33, 58\u201367 (2018)","journal-title":"IEEE Aerosp. Electron. Syst. Mag."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-020-01745-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-020-01745-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-020-01745-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T01:23:49Z","timestamp":1696469029000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-020-01745-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,29]]},"references-count":27,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["1745"],"URL":"https:\/\/doi.org\/10.1007\/s11760-020-01745-w","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2020,7,29]]},"assertion":[{"value":"4 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}