FedVC: Virtual Clients for Federated Autonomous Driving With Imbalanced Label Distribution
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DOI: 10.1109/tce.2025.3554180
Abstract: Federated learning in autonomous driving safeguards the privacy of individual vehicles during collaborative training by avoiding the exchange of raw data. These vehicles often suffer from imbalanced label distribution, making the federated learning model developed… read more here.
Keywords: distribution; virtual clients; federated learning; imbalanced label ... See more keywords