{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:51:45Z","timestamp":1775325105322,"version":"3.50.1"},"reference-count":92,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001695","name":"Japan Science and Technology Agency (JST) through Fusion Oriented REsearch for disruptive Science and Technology","doi-asserted-by":"publisher","award":["JPMJFR206S"],"award-info":[{"award-number":["JPMJFR206S"]}],"id":[{"id":"10.13039\/501100001695","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science (JSPS) through KAKENHI","doi-asserted-by":"publisher","award":["22H03609"],"award-info":[{"award-number":["22H03609"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tgrs.2023.3344670","type":"journal-article","created":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T19:36:58Z","timestamp":1702928218000},"page":"1-14","source":"Crossref","is-referenced-by-count":25,"title":["Frequency-Based Optimal Style Mix for Domain Generalization in Semantic Segmentation of Remote Sensing Images"],"prefix":"10.1109","volume":"62","author":[{"given":"Reo","family":"Iizuka","sequence":"first","affiliation":[{"name":"Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Chiba, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5586-6536","authenticated-orcid":false,"given":"Junshi","family":"Xia","sequence":"additional","affiliation":[{"name":"RIKEN Center for Advanced Intelligence Project, Tokyo, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7321-4590","authenticated-orcid":false,"given":"Naoto","family":"Yokoya","sequence":"additional","affiliation":[{"name":"Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Chiba, Japan"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2014.2347059"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_16"},{"key":"ref4","first-page":"1180","article-title":"Unsupervised domain adaptation by backpropagation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ganin"},{"key":"ref5","first-page":"1989","article-title":"CyCADA: Cycle-consistent adversarial domain adaptation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hoffman"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.223"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00503"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00261"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00116"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2022.3149950"},{"key":"ref12","article-title":"Generalizing from several related classification tasks to a new unlabeled sample","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"24","author":"Blanchard"},{"key":"ref13","first-page":"10","article-title":"Domain generalization via invariant feature representation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Muandet"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3178128"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3195549"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202133"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460528"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00219"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3096334"},{"key":"ref20","article-title":"Domain generalization with mixstyle","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Zhou"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00682"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.5772\/1796"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00787"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2599532"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00566"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01267-0_38"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00258"},{"key":"ref28","article-title":"Learning robust representations by projecting superficial statistics out","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Wang"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00970"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00262"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00699"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00656"},{"key":"ref33","article-title":"Gradient matching for domain generalization","author":"Shi","year":"2021","journal-title":"arXiv:2104.09937"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2018.8451318"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109115"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11596"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00821"},{"key":"ref38","article-title":"Auto-encoding variational Bayes","author":"Kingma","year":"2013","journal-title":"arXiv:1312.6114"},{"key":"ref39","article-title":"Generative adversarial nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Goodfellow"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00244"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01911"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.167"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2005.864170"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1117\/1.482725"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58517-4_33"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3152615"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00414"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01415"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00446"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00543"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.90"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.3390\/rs14030533"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2022.3214889"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref58","article-title":"ISPRS semantic labeling contest","author":"Rottensteiner","year":"2014"},{"key":"ref59","article-title":"LoveDA: A remote sensing land-cover dataset for domain adaptive semantic segmentation","author":"Wang","year":"2021","journal-title":"arXiv:2110.08733"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00031"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00139"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3104032"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.3390\/rs12071054"},{"key":"ref64","article-title":"Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory","author":"Zhu","year":"2022","journal-title":"arXiv:2208.07722"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3006161"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00104"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.3390\/rs12020275"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3068532"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00619"},{"key":"ref70","volume-title":"Flair: French Land Cover From Aerospace Imagery","author":"Garioud","year":"2023"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/jstars.2023.3268176"},{"key":"ref72","article-title":"Assessing out-of-domain generalization for robust building damage detection","volume-title":"Proc. NeurIPS Workshop Artif. Intell. Humanitarian Assistance Disaster Response","author":"Benson"},{"key":"ref73","article-title":"Averaging weights leads to wider optima and better generalization","author":"Izmailov","year":"2018","journal-title":"arXiv:1803.05407"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.03.005"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2022.103054"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2021.3061726"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2021.08.001"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/T-C.1974.223784"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1145\/103085.103089"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01225-0_29"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00087"},{"issue":"11","key":"ref82","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref84","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref87","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref88","article-title":"Rethinking Atrous convolution for semantic image segmentation","author":"Chen","year":"2017","journal-title":"arXiv:1706.05587"},{"key":"ref89","first-page":"1","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"25","author":"Krizhevsky"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11726-9_6"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01141"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19839-7_35"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/10354519\/10365190.pdf?arnumber=10365190","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T20:01:51Z","timestamp":1705089711000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10365190\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":92,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2023.3344670","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}