Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS
Author: | Rui SongORCiD, Liguo ZhouORCiD, Venkatnarayanan Lakshminarasimhan, Andreas FestagORCiD, Alois KnollORCiD |
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Language: | English |
Document Type: | Conference Paper |
Conference: | 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), Beijing and Macau (China) & online, 18.09. - 12.10.2022 |
Year of first Publication: | 2022 |
published in (English): | 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) |
Publisher: | IEEE |
Place of publication: | Piscataway |
ISBN: | 978-1-6654-6880-0 |
First Page: | 3502 |
Last Page: | 3508 |
Review: | peer-review |
Open Access: | nein |
Tag: | Computational modeling; Data models; Data privacy; Deep learning; Federated learning; Roads; Training |
Faculties / Institutes / Organizations: | Fakultät Elektro- und Informationstechnik |
CARISSMA Institute of Electric, Connected and Secure Mobility (C-ECOS) | |
Fraunhofer-Anwendungszentrum "Vernetzte Mobilität und Infrastruktur" | |
Release Date: | 2023/02/16 |