{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T19:27:02Z","timestamp":1783711622880,"version":"3.55.0"},"reference-count":115,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2020B090921003"],"award-info":[{"award-number":["2020B090921003"]}]},{"name":"Key Research and Development Program of Guangzhou","award":["202007050002"],"award-info":[{"award-number":["202007050002"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1811463"],"award-info":[{"award-number":["U1811463"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62173329"],"award-info":[{"award-number":["62173329"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Veh."],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1109\/tiv.2022.3197815","type":"journal-article","created":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T19:55:58Z","timestamp":1660593358000},"page":"456-465","source":"Crossref","is-referenced-by-count":68,"title":["Federated Vehicular Transformers and Their Federations: Privacy-Preserving Computing and Cooperation for Autonomous Driving"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1911-5791","authenticated-orcid":false,"given":"Yonglin","family":"Tian","sequence":"first","affiliation":[{"name":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0259-0118","authenticated-orcid":false,"given":"Jiangong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7429-031X","authenticated-orcid":false,"given":"Yutong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5625-2758","authenticated-orcid":false,"given":"Fei","family":"Yao","sequence":"additional","affiliation":[{"name":"North Automatic Control Technology Institute, Taiyuan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0008-0659","authenticated-orcid":false,"given":"Xiao","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3046859"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00141"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2021.3061907"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2017.7510598"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/tiv.2022.3154426"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2020.3040262"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3032227"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2021.3129534"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2021.1004057"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2021.3072679"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3017342"},{"key":"ref14","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","author":"Li","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2019.2955375"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3039456"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00252"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3003699"},{"key":"ref19","first-page":"652","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Qi","year":"2017"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00472"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2021.3065208"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2961128"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3026836"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2021.1003952"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/mits.2021.3116156"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3084827"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.2980671"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00178"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2019.2955851"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3044257"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.2987430"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3028424"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3137888"},{"key":"ref34","article-title":"Weakly supervised training of monocular 3D object detectors using wide baseline multi-view traffic camera data","author":"Howe","year":"2021"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9812038"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/lra.2022.3192802"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.02067"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC48978.2021.9564989"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/IV47402.2020.9304570"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2020.3036165"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM42002.2020.9322247"},{"key":"ref42","first-page":"1195","article-title":"Learning to communicate and correct pose errors","volume-title":"Proc. Conf. Robot Learn.","author":"Vadivelu","year":"2021"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19842-7_7"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8814148"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/tits.2022.3165791"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2022.3159664"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3093573"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3027319"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2019.2955907"},{"key":"ref50","first-page":"5998","article-title":"Attention is all you need","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Vaswani","year":"2017"},{"issue":"4","key":"ref51","first-page":"957","article-title":"Key problems and progress of vision transformers: The state of the art and prospects","volume":"48","author":"Tian","year":"2022","journal-title":"Acta Automatica Sinic"},{"key":"ref52","article-title":"Transformers in 3D point clouds: A survey","author":"Lu","year":"2022"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"ref54","article-title":"On the opportunities and risks of foundation models","author":"Bommasani","year":"2021"},{"key":"ref55","article-title":"Federated learning of deep networks using model averaging","volume":"2","author":"McMahan","year":"2016"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.2200\/s00960ed2v01y201910aim043"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref58","article-title":"Protection against reconstruction and its applications in private federated learning","author":"Bhowmick","year":"2018"},{"key":"ref59","first-page":"374","article-title":"Towards federated learning at scale: System design","volume-title":"Proc. Mach. Learn. Syst.","volume":"1","author":"Bonawitz","year":"2019"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106775"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/meditcom55741.2022.9928621"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000430"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.1900317"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/VNC51378.2020.9318386"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000558"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3081560"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3075683"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2021.3102121"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC55140.2022.9922064"},{"key":"ref70","article-title":"Intelligent transportation systems with the use of external infrastructure: A literature survey","author":"Cre","year":"2021"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2021.1004003"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/mits.2022.3190036"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2020.3044129"},{"issue":"4","key":"ref74","article-title":"Federated ecology: From federated data to federated intelligence","volume":"2","author":"Wang","year":"2020","journal-title":"Chin. J. Intell. Sci. Technol."},{"issue":"5","key":"ref75","article-title":"The dao to federated intelligence and decentralized autonomous federation of intelligent systems (DEFIS): From cognitive intelligence to ecological smartness","volume":"1","author":"Wang","year":"2021","journal-title":"Int. J. Intell. Control Syst."},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/ISSC.2018.8585340"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2020.1003246"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2019.2960944"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3145035"},{"key":"ref80","article-title":"A survey on visual transformer","author":"Han","year":"2020"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3227717"},{"key":"ref82","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Dosovitskiy","year":"2021"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"ref86","article-title":"Deformable DETR: Deformable transformers for end-to-end object detection","author":"Zhu","year":"2020"},{"key":"ref87","first-page":"12077","article-title":"SegFormer: Simple and efficient design for semantic segmentation with transformers","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Xie","year":"2021"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.00135"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00911"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58517-4_31"},{"key":"ref91","article-title":"TransGAN: Two transformers can make one strong GAN","author":"Jiang"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-021-0229-5"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00700"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2020.1003300"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2006.962"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2014.6942560"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2015.7301390"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58610-2_30"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636241"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9575242"},{"key":"ref102","article-title":"How much position information do convolutional neural networks encode","author":"Islam","year":"2020"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.298"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00988"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01644"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00290"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00827"},{"key":"ref108","article-title":"Real-time 3D single object tracking with transformer","author":"Jiayao","year":"2022","journal-title":"IEEE Trans. Multimedia"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01667"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00116"},{"key":"ref111","article-title":"Split learning for health: Distributed deep learning without sharing raw patient data","author":"Vepakomma","year":"2018"},{"key":"ref112","article-title":"Federated split vision transformer for COVID-19 CXR diagnosis using task-agnostic training","author":"Park","year":"2021"},{"key":"ref113","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Int. Conf. Mach. Learn. Workshops","volume":"3","author":"Lee","year":"2013"},{"key":"ref114","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Tarvainen","year":"2017"},{"key":"ref115","first-page":"130","article-title":"Design method of secure computing protocol for deep neural network","volume":"6","author":"Bi","year":"2020","journal-title":"Chin. J. Netw. Inf. Secur."}],"container-title":["IEEE Transactions on Intelligent Vehicles"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274857\/9927386\/09857660.pdf?arnumber=9857660","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T05:08:29Z","timestamp":1709356109000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9857660\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":115,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tiv.2022.3197815","relation":{},"ISSN":["2379-8904","2379-8858"],"issn-type":[{"value":"2379-8904","type":"electronic"},{"value":"2379-8858","type":"print"}],"subject":[],"published":{"date-parts":[[2022,9]]}}}