Use of learning methods for gender and age classification based on front shot face images

Document Type : Research Paper


Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq


Facial system estimation is a mature and in-depth research technique in age and gender. Estimation accuracy is an important indicator for evaluating algorithms. By using deep learning-based learning (DL) and machine learning, this work provides a robust approach to estimating the type and age of different external environment changes based on two different algorithms, comparing the results, and analyzing the performance of the two algorithms. The algorithm was evaluated using a data set that is considered the basis in this area of the face estimation system, namely (IMDB-WIKI) an image. The basis of the work depends on the external appearance and the front section. The results obtained: DL(Effacint-B3) AGE Accuracy=0.99 Gender Accuracy=0.97 ML(SVM) AGE Accuracy=0.87 Gender Accuracy=0.97.


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Volume 14, Issue 3
March 2023
Pages 327-342
  • Receive Date: 07 July 2022
  • Revise Date: 16 August 2022
  • Accept Date: 20 September 2022
  • First Publish Date: 03 October 2022