AGE RECOGNITION BY FACE IMAGES USING CONVOLUTIONAL NEURAL NETWORKS
D. V. Pakulich1,2, S. A. Yakimov2, S. A. Alyamkin2
1Novosibirsk State University, Novosibirsk, Russia
2JSC 'Ekspasoft', Novosibirsk, Russia
Keywords: свёрточные нейронные сети, распознавание возраста, глубокие нейронные сети, компьютерное зрение, convoluted neural network, age recognition, deep neural networks, computer vision
Abstract
A problem of age recognition by 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 markings 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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