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Notes on connected vehicles
2 notes
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
The paper presents an online anomaly detection framework for connected vehicles that uses a deep Q-network with self-attention to select suitable detectors, an ensemble of statistical drift detectors to monitor input…
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
The paper proposes an online anomaly detection framework for autonomous cyber-physical systems (CPS), specifically connected vehicles, that combines three coordinated mechanisms: a deep Q-network with self-attention to…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
