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Embedded Vision Systems Group, Computer Vision Laboratory, AGH University of Krakow,Poland
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Event-based graph neural networks running on FPGAs can outperform spiking neural networks in audio classification by up to 19.3% while using fewer resources and slashing latency.
Achieving up to 31.4% memory savings in GCNs for embedded systems with only a modest accuracy drop could revolutionize real-time event-based vision processing.
