The paper reports a differentially private federated semantic segmentation method for autonomous driving, with accuracy gains claimed from 81.5% to 88.7% on RGB and from 79.3% to 86.9% on SEG data, though inconsistent numbers appear elsewhere.
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Federated Learning-based Semantic Segmentation for Lane and Object Detection in Autonomous Driving
The paper reports a differentially private federated semantic segmentation method for autonomous driving, with accuracy gains claimed from 81.5% to 88.7% on RGB and from 79.3% to 86.9% on SEG data, though inconsistent numbers appear elsewhere.