arXiv:2408.07225v1 Announce Type: new
Abstract: The need for reliable identification of children in various emerging applications has sparked interest in leveraging child face recognition technology. This study introduces a longitudinal approach to enrollment and verification accuracy for child face recognition, focusing on the YFA database collected by Clarkson University CITeR research group over an 8 year period, at 6 month intervals.
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Longitudinal Evaluation of Child Face Recognition and the Impact of Underlying Age
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