Longitudinal Evaluation of Child Face Recognition and the Impact of Underlying Age
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866910565077614592 |
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| author | Singh, Surendra Bahmani, Keivan Schuckers, Stephanie |
| author_facet | Singh, Surendra Bahmani, Keivan Schuckers, Stephanie |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_07225 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Longitudinal Evaluation of Child Face Recognition and the Impact of Underlying Age Singh, Surendra Bahmani, Keivan Schuckers, Stephanie Computer Vision and Pattern Recognition Artificial Intelligence 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. |
| title | Longitudinal Evaluation of Child Face Recognition and the Impact of Underlying Age |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2408.07225 |