{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T19:26:59Z","timestamp":1783711619990,"version":"3.55.0"},"reference-count":28,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3428369","type":"journal-article","created":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T18:23:17Z","timestamp":1721067797000},"page":"138076-138085","source":"Crossref","is-referenced-by-count":6,"title":["Generating Synthetic Vehicle Data Using Decentralized Generative Adversarial Networks"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8506-3198","authenticated-orcid":false,"given":"Basem","family":"Shaker","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1075-9603","authenticated-orcid":false,"given":"Gastone","family":"Pietro Rosati Papini","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9784-3973","authenticated-orcid":false,"given":"Matteo","family":"Saveriano","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5107-2942","authenticated-orcid":false,"given":"Kuo-Yun","family":"Liang","sequence":"additional","affiliation":[{"name":"Scania CV AB, Södertälje, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2023.3273896"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298673"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.46"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.agwat.2020.106303"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5997"},{"key":"ref8","article-title":"Time-series generative adversarial networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yoon"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2019.00095"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3459992"},{"key":"ref12","article-title":"Decentralized learning of generative adversarial networks from non-iid data","author":"Yonetani","year":"2019","journal-title":"arXiv:1905.09684"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3309858"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3423211.3425688"},{"key":"ref15","article-title":"FedGAN: Federated generative adversarial networks for distributed data","author":"Rasouli","year":"2020","journal-title":"arXiv:2006.07228"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/BigData55660.2022.10020158"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3559540"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/WACVW52041.2021.00023"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.05957"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-019-00619-1"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10578-9_23"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"ref23","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Kingma"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/72.279188"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref26","article-title":"Diffusion-based time series imputation and forecasting with structured state space models","author":"Alcaraz","year":"2022","journal-title":"Trans. Mach. Learn. Res."},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2022.3197950"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2022.3228594"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10380310\/10597551.pdf?arnumber=10597551","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,9]],"date-time":"2024-10-09T18:08:36Z","timestamp":1728497316000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10597551\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3428369","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}