{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T19:00:12Z","timestamp":1762455612976,"version":"build-2065373602"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62103414"],"award-info":[{"award-number":["62103414"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Aeronautical Science Foundation of China","award":["2024Z031051001"],"award-info":[{"award-number":["2024Z031051001"]}]},{"DOI":"10.13039\/501100001809","name":"2024 Self-Deployed Research and Development Project of China Tower Corporation Ltd","doi-asserted-by":"publisher","award":["GPDI-ZB-2024-01141"],"award-info":[{"award-number":["GPDI-ZB-2024-01141"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tgrs.2025.3624835","type":"journal-article","created":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T17:51:35Z","timestamp":1761241895000},"page":"1-14","source":"Crossref","is-referenced-by-count":1,"title":["Is Meta-Learning Effective for Few-Shot Hyperspectral Image Classification?"],"prefix":"10.1109","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6520-1418","authenticated-orcid":false,"given":"Li","family":"Shen","sequence":"first","affiliation":[{"name":"Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1309-589X","authenticated-orcid":false,"given":"Yangzhu","family":"Wang","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0011-7433","authenticated-orcid":false,"given":"Xiaoman","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6995-7367","authenticated-orcid":false,"given":"Huaxin","family":"Qiu","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}]},{"given":"Zhenyang","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Tower Corporation Ltd., Beijing, China"}]},{"given":"Chang","family":"Nie","sequence":"additional","affiliation":[{"name":"China Tower Corporation Ltd., Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2152-4172","authenticated-orcid":false,"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"Beihang University, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2646420"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2023.3328139"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/cancers13184593"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2023.3284846"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108586"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413832"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.02.005"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3298851"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3407201"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3465225"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3386256"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2025.3531709"},{"volume-title":"Learning to Learn With Gradients","year":"2018","author":"Finn","key":"ref13"},{"key":"ref14","first-page":"3770","article-title":"Two sides of meta-learning evaluation: In vs. out of distribution","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Setlur"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1002\/0470124628"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3233591"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3149947"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3233885"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2872830"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3185795"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2903719"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3218284"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2017.2762087"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CIS-RAM61939.2024.10672889"},{"article-title":"220 band aviris hyperspectral image data set: June 12, 1992 Indian pine test site 3","year":"1992","author":"Baumgardner","key":"ref25"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2015.2416693"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2018.2816958"},{"volume-title":"Hyperspectral Remote Sensing Scenes-Grupo De Inteligencia Computacional (GIC)","year":"2021","author":"Grana","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2934218"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.111197"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2025.3528442"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3232784"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125453"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3385478"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3303319"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3476116"},{"article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Dosovitskiy","key":"ref37"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref39","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Touvron"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00010"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00060"},{"article-title":"A time series is worth 64 words: Long-term forecasting with transformers","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Nie","key":"ref42"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614851"},{"key":"ref44","first-page":"12409","article-title":"TSLANet: Rethinking transformers for time series representation learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Eldele"},{"key":"ref45","first-page":"12389","article-title":"WITRAN: Water-wave information transmission and recurrent acceleration network for long-range time series forecasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Jia"},{"key":"ref46","first-page":"28708","article-title":"Masked autoencoders that listen","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Huang"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10446348"},{"key":"ref48","first-page":"3807","article-title":"EAT: Self-supervised pre-training with efficient audio transformer","volume-title":"Proc. 33rd Int. Joint Conf. Artif. Intell.","author":"Chen"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2008.922034"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2765364"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128751"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3402364"},{"key":"ref53","article-title":"Gaussian error linear units (GELUs)","author":"Hendrycks","year":"2016","journal-title":"arXiv:1606.08415"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1080\/10485250902952435"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/36\/10807682\/11215827.pdf?arnumber=11215827","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T18:53:14Z","timestamp":1762455194000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11215827\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2025.3624835","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"type":"print","value":"0196-2892"},{"type":"electronic","value":"1558-0644"}],"subject":[],"published":{"date-parts":[[2025]]}}}