Age Recognition from Facial Images using Convolutional Neural Networks

D. V. Pakulich, S. A. Yakimov, S. A. Alyamkin

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)255-262
Number of pages8
JournalOptoelectronics, Instrumentation and Data Processing
Issue number3
Publication statusPublished - 1 May 2019


  • age recognition
  • computer vision
  • convolutional neural network
  • deep neural networks


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