{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T03:29:09Z","timestamp":1775014149475,"version":"3.50.1"},"reference-count":53,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"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":["62002398"],"award-info":[{"award-number":["62002398"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"publisher","award":["2023A1515012895"],"award-info":[{"award-number":["2023A1515012895"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001381","name":"National Research Foundation Singapore and DSO National Laboratories under the AI Singapore Program","doi-asserted-by":"publisher","award":["AISG2-RP-2020-019"],"award-info":[{"award-number":["AISG2-RP-2020-019"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]},{"name":"RIE 2020 Advanced Manufacturing and Engineering (AME) Programmatic Fund, Singapore","award":["A20G8b0102"],"award-info":[{"award-number":["A20G8b0102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1109\/tits.2024.3357138","type":"journal-article","created":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T18:57:33Z","timestamp":1707332253000},"page":"9659-9674","source":"Crossref","is-referenced-by-count":20,"title":["AFM3D: An Asynchronous Federated Meta-Learning Framework for Driver Distraction Detection"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9883-5289","authenticated-orcid":false,"given":"Sheng","family":"Liu","sequence":"first","affiliation":[{"name":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6287-8095","authenticated-orcid":false,"given":"Linlin","family":"You","sequence":"additional","affiliation":[{"name":"School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9965-0948","authenticated-orcid":false,"given":"Rui","family":"Zhu","sequence":"additional","affiliation":[{"name":"Institute of High Performance Computing, A*STAR, Fusionopolis, Singapore"}]},{"given":"Bing","family":"Liu","sequence":"additional","affiliation":[{"name":"BYD Auto Company Ltd., Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3606-0553","authenticated-orcid":false,"given":"Rui","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6893-8650","authenticated-orcid":false,"given":"Han","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9307-2120","authenticated-orcid":false,"given":"Chau","family":"Yuen","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronics Engineering, Nanyang Technological University, Jurong West, Singapore"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2917866"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3270879"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2020.105579"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3126231"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.105881"},{"key":"ref6","article-title":"Unleashing the power of edge-cloud generative AI in mobile networks: A survey of AIGC services","author":"Xu","year":"2023","journal-title":"arXiv:2303.16129"},{"key":"ref7","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03583-3"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3188556"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/jiot.2024.3353793"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11091393"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/6626471"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2021.3077893"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/tits.2023.3316203"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2020.2973651"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/tits.2022.3157056"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3205596"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3079209"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00100"},{"key":"ref20","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Finn"},{"key":"ref21","first-page":"1920","article-title":"Online meta-learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Finn"},{"key":"ref22","article-title":"On first-order meta-learning algorithms","author":"Nichol","year":"2018","journal-title":"arXiv:1803.02999"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00233"},{"key":"ref24","first-page":"3557","article-title":"Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Fallah"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1002\/int.22951"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-10983-6_13"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3390\/math10122039"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/math11081867"},{"key":"ref29","first-page":"2351","article-title":"Ensemble distillation for robust model fusion in federated learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Lin"},{"key":"ref30","first-page":"12878","article-title":"Data-free knowledge distillation for heterogeneous federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhu"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00993"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00377"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3243622"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3118435"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3527621"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3147792"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3458817.3476211"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2023.3332770"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/mnet.2023.3321519"},{"key":"ref40","article-title":"Asynchronous federated optimization","author":"Xie","year":"2019","journal-title":"arXiv:1903.03934"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9378161"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/SPAWC51858.2021.9593194"},{"key":"ref43","first-page":"17202","article-title":"Sharper convergence guarantees for asynchronous SGD for distributed and federated learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Koloskova"},{"key":"ref44","article-title":"Real-time distracted driver posture classification","author":"Abouelnaga","year":"2017","journal-title":"arXiv:1706.09498"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01057"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref48","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Touvron"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_8"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"key":"ref52","article-title":"Towards understanding and mitigating dimensional collapse in heterogeneous federated learning","author":"Shi","year":"2022","journal-title":"arXiv:2210.00226"},{"key":"ref53","article-title":"Federated meta-learning with fast convergence and efficient communication","author":"Chen","year":"2018","journal-title":"arXiv:1802.07876"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/10621861\/10423999.pdf?arnumber=10423999","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T02:49:19Z","timestamp":1733885359000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10423999\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":53,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tits.2024.3357138","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8]]}}}