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Carry-Through Checksum: A Lightweight Fault-Detection for CNN Inference at the Edge

Nazarevych, Kyrylo et al.
arXiv (OAI Expanded) · Papers
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Convolutional Neural Networks (CNNs) are increasingly deployed in safety-critical edge applications, where soft errors can silently corrupt inference outputs and lead to unsafe decisions. Such applications typically rely on resource-constrained embedded GPUs, requiring fault detection and mitigation
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