{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T16:40:21Z","timestamp":1781973621648,"version":"3.54.5"},"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:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA0310502"],"award-info":[{"award-number":["XDA0310502"]}]},{"name":"Future Star of Aerospace Information Research Institute, Chinese Academy of Sciences","award":["E3Z10701"],"award-info":[{"award-number":["E3Z10701"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tgrs.2025.3623125","type":"journal-article","created":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T17:49:28Z","timestamp":1760982568000},"page":"1-20","source":"Crossref","is-referenced-by-count":3,"title":["SAFE: Self-Adjustment Federated Learning Framework for Remote Sensing Collaborative Perception"],"prefix":"10.1109","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4430-4164","authenticated-orcid":false,"given":"Xiaohe","family":"Li","sequence":"first","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haohua","family":"Wu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiahao","family":"Li","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2696-8234","authenticated-orcid":false,"given":"Zide","family":"Fan","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaixin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinming","family":"Li","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2803-0869","authenticated-orcid":false,"given":"Yunping","family":"Ge","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Aerospace Information Research Institute, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3252544"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3243238"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3363057"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3258666"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3373033"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.106854"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106775"},{"key":"ref8","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume-title":"Proc. 3rd Mach. Learn. Syst. Conf.","author":"Li"},{"key":"ref9","article-title":"Divergence-aware federated self-supervised learning","author":"Zhuang","year":"2022","journal-title":"arXiv:2204.04385"},{"key":"ref10","article-title":"Federated self-supervised learning for heterogeneous clients","author":"Makhija","year":"2022","journal-title":"arXiv:2205.12493"},{"key":"ref11","first-page":"1","article-title":"MocoSFL: Enabling cross-client collaborative self-supervised learning","volume-title":"Proc. 11th Int. Conf. Learn. Represent. (ICLR)","author":"Li"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3390\/rs16132504"},{"key":"ref13","first-page":"2074","article-title":"Navigating data heterogeneity in federated learning a semi-supervised federated object detection","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Kim"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/MIPR.2018.00027"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17219"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00487"},{"key":"ref18","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS56603.2022.00107"},{"key":"ref20","first-page":"7611","article-title":"Tackling the objective inconsistency problem in heterogeneous federated optimization","volume-title":"Proc. NIPS","author":"Wang"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2023.3332255"},{"key":"ref22","first-page":"8230","article-title":"G-mixup: Graph data augmentation for graph classification","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Han"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.5555\/3495724.3497510"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00995"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref27","article-title":"Fed-focal loss for imbalanced data classification in federated learning","author":"Sarkar","year":"2020","journal-title":"arXiv:2011.06283"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3271517"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01104"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73010-8_18"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01291"},{"key":"ref32","first-page":"28403","article-title":"Learning adaptive and view-invariant vision transformer for real-time UAV tracking","volume-title":"Proc. 41st Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3390\/rs16061031"},{"key":"ref34","article-title":"LEGNet: Lightweight edge-Gaussian driven network for low-quality remote sensing image object detection","author":"Lu","year":"2025","journal-title":"arXiv:2503.14012"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS53475.2024.10641423"},{"key":"ref36","first-page":"3519","article-title":"Similarity of neural network representations revisited","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kornblith"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2018.01.004"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2675998"},{"key":"ref39","article-title":"LoveDA: A remote sensing land-cover dataset for domain adaptive semantic segmentation","author":"Wang","year":"2021","journal-title":"arXiv:2110.08733"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.3390\/rs10060964"},{"key":"ref41","article-title":"Not all federated learning algorithms are created equal: A performance evaluation study","author":"Baumgart","year":"2024","journal-title":"arXiv:2403.17287"},{"key":"ref42","first-page":"5132","article-title":"SCAFFOLD: Stochastic controlled averaging for federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Karimireddy"},{"key":"ref43","article-title":"Adaptive federated optimization","author":"Reddi","year":"2020","journal-title":"arXiv:2003.00295"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.33395\/sinkron.v8i3.12702"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_8"},{"key":"ref48","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tan"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2019.00095"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref52","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","author":"Harry Hsu","year":"2019","journal-title":"arXiv:1909.06335"},{"key":"ref53","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Ren"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/3402597.3402605"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/36\/10807682\/11208169.pdf?arnumber=11208169","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T18:41:22Z","timestamp":1763404882000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11208169\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2025.3623125","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}