Deploying face identification, anti-spoofing, and low-power wakeup.
Accurate face verification has long been considered a challenge due to the number of variables, ranging from lighting to pose and facial expression.
This white paper looks at a new approach — combining classic and modern machine learning (deep learning) techniques — that achieves 98.36% accuracy, running efficiently on Arm ML-optimized platforms, and addressing key security issues such as multi-user verification, as well as anti-spoofing.
Click here to read more.
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