Age Recognition from Facial Images using Convolutional Neural Networks

被引：4
|
作者：
Pakulich, D. V. [1 ,2 ]
Yakimov, S. A. [2 ]
Alyamkin, S. A. [2 ]
机构：
[1] Novosibirsk State Univ, Ul Pirogova 2, Novosibirsk 630090, Russia
[2] JSC Expasoft, Ul Nikolaeva 11, Novosibirsk 630090, Russia
来源：
OPTOELECTRONICS INSTRUMENTATION AND DATA PROCESSING | 2019年 / 55卷 / 03期
关键词：
convolutional neural network; age recognition; deep neural networks; computer vision;
D O I：
10.3103/S8756699019030075
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
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.
引用
收藏
页码：255 / 262
页数：8
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