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1 Ergebnisse
1
Federated Learning for Pedestrian Detection in Vehicular Ne..:
, In:
2023 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)
,
Kumec, Feyzi Ege
;
Reyhanoglu, Aslihan
;
Kar, Emrah
... - p. 150-154 , 2023
Link:
https://doi.org/10.1109/BlackSeaCom58138.2023.10299783
RT T1 <cTitle>2023 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)</cTitle>: T1 <Title>Federated Learning for Pedestrian Detection in Vehicular Networks</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10299783&Exemplar=1&LAN=DE A1 Kumec, Feyzi Ege A1 Reyhanoglu, Aslihan A1 Kar, Emrah A1 Turan, Bugra A1 Coleri, Sinem A1 Bennis, Mehdi A1 Elgabli, Anis A1 Gunduz, Deniz A1 Karaagac, Sercan YR 2023 K1 Training K1 Pedestrians K1 Federated learning K1 Computational modeling K1 Computer architecture K1 Road safety K1 Robustness K1 federated learning K1 vehicular networks K1 Cellular Vehicle-to-Everything (C-V2X) K1 LTE K1 pedestrian detection K1 PC5 K1 image classification K1 image detection K1 image processing SP 150 OP 154 LK http://dx.doi.org/https://doi.org/10.1109/BlackSeaCom58138.2023.10299783 DO https://doi.org/10.1109/BlackSeaCom58138.2023.10299783 SF ELIB - SuUB Bremen
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