Age Recognition from Facial Images using Convolutional Neural Networks
- Авторы: Pakulich D.V.1,2, Yakimov S.A.2, Alyamkin S.A.2
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Учреждения:
- Novosibirsk State University
- JSC “Expasoft”
- Выпуск: Том 55, № 3 (2019)
- Страницы: 255-262
- Раздел: Analysis and Synthesis of Signals and Images
- URL: https://journals.rcsi.science/8756-6990/article/view/212753
- DOI: https://doi.org/10.3103/S8756699019030075
- ID: 212753
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Аннотация
A problem of age recognition from a human’s face is developed with the popularization of convolutional neural networks. They make it possible to determine the specific features of faces, unseen by a human eye, and interpret them as age characteristics. Existing approaches to age recognition are analyzed. Data from existing sets for learning with subsequent correction for reducing the errors made in labels by acquisition algorithms are used. Neural networks are taught and tested using the resulting data. There is a problem with head rotation, whose solution is carried out using the images of faces rotated using the PRNet neural network.
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Об авторах
D. Pakulich
Novosibirsk State University; JSC “Expasoft”
Автор, ответственный за переписку.
Email: d.pakulich@expasoft.ru
Россия, ul. Pirogova 2, Novosibirsk, 630090; ul. Nikolaeva 11, Novosibirsk, 630090
S. Yakimov
JSC “Expasoft”
Email: d.pakulich@expasoft.ru
Россия, ul. Nikolaeva 11, Novosibirsk, 630090
S. Alyamkin
JSC “Expasoft”
Email: d.pakulich@expasoft.ru
Россия, ul. Nikolaeva 11, Novosibirsk, 630090
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