Aug 1, 2024 · This study introduces a longitudinal approach to enrollment and verification accuracy for child face recognition, focusing on the YFA database ...
Aug 17, 2024 · This study introduces a longitudinal approach to enrollment and verification accuracy for child face recognition, focusing on the YFA database ...
Aug 14, 2024 · Overview. The study examines a longitudinal approach to accuracy for child face recognition over an 8-year period.
The average TAR across all age groups is 98.52% with a FAR of 0.1% with a 2-year age verification gap and drops to 95.68 with a 4-year age gap. However, this ...
This study introduces a longitudinal approach to enrollment and verification accuracy for child face recognition, focusing on the YFA database collected by ...
Apr 4, 2022 · In this work, we introduce the Young Face Aging (YFA) dataset for analyzing the performance of face recognition systems over short age-gaps in children.
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Nov 10, 2017 · We present a longitudinal study of face recognition performance on Children Longitudinal Face (CLF) dataset containing 3,682 face images of ...
This work explores the challenges of biological changes due to maturation, i.e. the face grows longer and wider, the nose expands, the lips widen, etc, i.e. ...
MORPH-II: The academic MORPH dataset is longitudinal and controlled dataset. This dataset is used to evaluate the performance of short age-gap (up to 5 years) ...
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Feb 1, 2019 · We longitudinally measured hemodynamic responses to frontal and profile faces in 14 infants at 6 time points ranging from 3 to 8 months of age.
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