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Use of learning methods for gender and age classification based on front shot face images | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 27، دوره 14، شماره 3، خرداد 2023، صفحه 327-342 اصل مقاله (1.86 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6996 | ||
| نویسندگان | ||
| Hussein Razak Hayawi* ؛ Alyaa Al-Barrak | ||
| Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq | ||
| تاریخ دریافت: 16 تیر 1401، تاریخ بازنگری: 25 مرداد 1401، تاریخ پذیرش: 29 شهریور 1401 | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Face System؛ Estimation؛ Age؛ Gender؛ Deep Learning؛ Efficient-B3؛ IMDB-WIKI | ||
| مراجع | ||
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