distributed-and-edge-ai

2025 Scientific Report • April 1, 2026

Low-latency motion detection with event graphs

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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2025 Scientific Report • April 1, 2026

Toward smart acquisition systems

Advances in Edge computing and AI have made integrating analysis capabilities directly into acquisition systems a reality.

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2025 Scientific Report • April 1, 2026

A federated learning approach with distributed multi-source domain adaptation for serverless collaborative learning

CEA-List developed De-FedDaDiL, a fully distributed method for multi-source domain adaptation (MSDA).

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2025 Scientific Report • April 1, 2026

Adaptive learning to counter catastrophic forgetting and concept drift in federated learning for optimized electric charging station management with predictive capabilities and data privacy

CEA-List developed federated learning algorithms to predict charging station occupancy in real time without sharing sensitive user data.

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