MOTE replaces fixed face embeddings with per-identity binary classifiers trained using KDE-generated synthetic samples, improving gender fairness and privacy at the cost of storage and enrollment time.
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A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through Personalized Neural Networks
MOTE replaces fixed face embeddings with per-identity binary classifiers trained using KDE-generated synthetic samples, improving gender fairness and privacy at the cost of storage and enrollment time.