{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,29]],"date-time":"2026-03-29T06:03:53Z","timestamp":1774764233146,"version":"3.50.1"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3192454","type":"journal-article","created":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T19:34:33Z","timestamp":1658345673000},"page":"80565-80574","source":"Crossref","is-referenced-by-count":47,"title":["Privacy-Preserving Federated Transfer Learning for Driver Drowsiness Detection"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3415-7172","authenticated-orcid":false,"given":"Linlin","family":"Zhang","sequence":"first","affiliation":[{"name":"Graduate School of Science and Technology, Keio University, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2421-9862","authenticated-orcid":false,"given":"Hideo","family":"Saito","sequence":"additional","affiliation":[{"name":"Graduate School of Science and Technology, Keio University, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Yang","sequence":"additional","affiliation":[{"name":"China Auto Information Technology Co., Ltd., Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiajie","family":"Wu","sequence":"additional","affiliation":[{"name":"China Automotive Technology and Research Center Co., Ltd., Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"3","key":"ref1","first-page":"4245","article-title":"Driver drowsiness detection system and techniques: A review","volume":"5","author":"Saini","year":"2014","journal-title":"Int. J. Comput. Sci. Inf. Technol."},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2914373"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2462084"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.5013\/IJSSST.a.20.S2.37"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00027"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294368"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-54526-4_9"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2963960"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-57959-7"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC48978.2021.9564936"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2021.09.007"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/tii.2022.3140806"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/s22082983"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2021-0064"},{"key":"ref15","article-title":"Privacy-preserving similarity calculation of speaker features using fully homomorphic encryption","volume-title":"arXiv:2202.07994","author":"Rahulamathavan","year":"2022"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ElConRus51938.2021.9396482"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106775"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-020-00247-z"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/comst.2021.3090430"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2020.3004555"},{"key":"ref21","first-page":"3320","article-title":"How transferable are features in deep neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Yosinski"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3034343"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1117\/1.JMI.3.3.034501"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104244"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58583-9_21"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00432"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/icc.2019.8761267"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/jiot.2020.2987958"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/tifs.2020.2988575"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-020-00162-3"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.2298\/CSIS190923022O"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3363207"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2021.3110813"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3025818"},{"key":"ref36","article-title":"Long-term multi-granularity deep framework for driver drowsiness detection","volume-title":"arXiv:1801.02325","author":"Lyu","year":"2018"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2019EDL8079"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-54526-4_12"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2557642.2563678"},{"key":"ref40","article-title":"Driver drowsiness detection using ensemble convolutional neural networks on YawDD","volume-title":"arXiv:2112.10298","author":"Salman","year":"2021"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1090\/1\/012037"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-44689-5_17"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICAIS50930.2021.9395975"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICECA52323.2021.9676050"},{"key":"ref45","article-title":"FedSup: A communication-efficient federated learning fatigue driving behaviors supervision framework","volume-title":"arXiv:2104.12086","author":"Zhao","year":"2021"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/jsac.2019.2904348"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-021-00519-2"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/tpds.2020.2975189"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09833516.pdf?arnumber=9833516","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T06:51:10Z","timestamp":1706770270000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9833516\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3192454","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}