Researchers develop EdgeFace, a face recognition model for resource-constrained edge devices

Scientists have developed EdgeFace, a novel face recognition model optimized for use on devices with limited processing power and storage. This lightweight face recognition network is inspired by the hybrid architecture of EdgeNeXt, which combines the strengths of convolutional neural networks (CNNs) and transformers to perform accurate face recognition while conserving computational resources.

Typical facial recognition systems rely on deep neural networks that, despite their accuracy, demand extensive memory and processing capabilities, rendering them impractical for use on edge …

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