Event-driven cameras provide low-latency motion detection. Our method leverages asynchronous event graphs that take full advantage of the cameras’ high time resolution to detect motion with very low latency (just 50 milliseconds) while reducing the number of operations 48-fold compared to the state of the art.
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Advances in Edge computing and AI have made integrating analysis capabilities directly into acquisition systems a reality.
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CEA-List developed De-FedDaDiL, a fully distributed method for multi-source domain adaptation (MSDA).
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CEA-List developed federated learning algorithms to predict charging station occupancy in real time without sharing sensitive user data.
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