{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T02:54:59Z","timestamp":1784948099251,"version":"3.55.0"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFB3900502"],"award-info":[{"award-number":["2021YFB3900502"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["JQ20021"],"award-info":[{"award-number":["JQ20021"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tip.2023.3243853","type":"journal-article","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T18:36:30Z","timestamp":1677090990000},"page":"1498-1512","source":"Crossref","is-referenced-by-count":319,"title":["Single-Source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification"],"prefix":"10.1109","volume":"32","author":[{"given":"Yuxiang","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Information and Electronics and the Beijing Key Laboratory of Fractional Signals and Systems, Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7015-7335","authenticated-orcid":false,"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information and Electronics and the Beijing Key Laboratory of Fractional Signals and Systems, Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8931-8407","authenticated-orcid":false,"given":"Weidong","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Institute for Ocean Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5243-7189","authenticated-orcid":false,"given":"Ran","family":"Tao","sequence":"additional","affiliation":[{"name":"School of Information and Electronics and the Beijing Key Laboratory of Fractional Signals and Systems, Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8354-7500","authenticated-orcid":false,"given":"Qian","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Mississippi State University, starkville, Mississippi State MS, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3118977"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2772836"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3144017"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3004261"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2761542"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3109872"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3046756"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3185795"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3233885"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0069"},{"issue":"1","key":"ref11","first-page":"2030","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"Ganin","year":"2015","journal-title":"J. Mach. Learn. Res."},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00088"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.07.010"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2988928"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2997863"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/628"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00321"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-023-06324-x"},{"key":"ref19","first-page":"1","article-title":"Generalizing to unseen domains via adversarial data augmentation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Volpi"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.7003"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00029"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9206635"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107124"},{"key":"ref24","first-page":"5102","article-title":"Domain agnostic learning with disentangled representations","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Peng"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3360309"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_35"},{"key":"ref27","article-title":"Domain generalization via optimal transport with metric similarity learning","author":"Zhou","year":"2020","journal-title":"arXiv:2007.10573"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312.6114"},{"key":"ref29","first-page":"53","article-title":"Generative adversarial nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Goodfellow"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.48550\/arxiv.1710.09412"},{"key":"ref32","article-title":"Representation learning with contrastive predictive coding","author":"van den Oord","year":"2018","journal-title":"arXiv:1807.03748"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00393"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58621-8_45"},{"key":"ref37","first-page":"1","article-title":"Batch-instance normalization for adaptively style-invariant neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Nam"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00194"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-14085-4_21"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1515\/mathm-2020-0103"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2951445"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00087"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00858"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2014.2305441"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2018.2798161"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2019.111322"},{"key":"ref47","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"Proc. 13th Int. Conf. Artif. Intell. Statist.","author":"Glorot"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref49","article-title":"Exact solutions to the nonlinear dynamics of learning in deep linear neural networks","author":"Saxe","year":"2013","journal-title":"arXiv:1312.6120"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/9991910\/10050427.pdf?arnumber=10050427","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T18:24:15Z","timestamp":1707848655000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10050427\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/tip.2023.3243853","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}