CNN-based Gender Prediction in Uncontrolled Environments

Kazım Yıldız; Engin Güneş; Anil Bas

doi:10.29130/dubited.763427

EN TR

CNN-based Gender Prediction in Uncontrolled Environments

Abstract

With the increasing amount of data produced and collected, the use of artificial intelligence technologies has become inevitable. By using deep learning techniques from these technologies, high performance can be achieved in tasks such as classification and face analysis in the fields of image processing and computer vision. In this study, Convolutional Neural Networks (CNN), one of the deep learning algorithms, was used. The model created with this algorithm was trained with facial images and gender prediction was made. As a result of the experiments, 93.71% success rate was achieved on the VGGFace2 data set and 85.52% success rate on the Adience data set. The aim of the study is to classify low-resolution images with high accuracy.

Keywords

CNN, VGGFace2, Adience, Image classification, Gender classification

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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Kazım Yıldız ^*
0000-0001-6999-1410
Türkiye

Engin Güneş
0000-0003-3757-5214
Türkiye

Anil Bas
0000-0002-3833-6023
Türkiye

Publication Date

April 25, 2021

Submission Date

July 3, 2020

Acceptance Date

February 2, 2021

Published in Issue

Year 2021 Volume: 9 Number: 2

DOI

https://doi.org/10.29130/dubited.763427

IZ

https://izlik.org/JA99YA53NF

APA

Yıldız, K., Güneş, E., & Bas, A. (2021). CNN-based Gender Prediction in Uncontrolled Environments. Duzce University Journal of Science and Technology, 9(2), 890-898. https://doi.org/10.29130/dubited.763427

AMA

1.Yıldız K, Güneş E, Bas A. CNN-based Gender Prediction in Uncontrolled Environments. DUBİTED. 2021;9(2):890-898. doi:10.29130/dubited.763427

Chicago

Yıldız, Kazım, Engin Güneş, and Anil Bas. 2021. “CNN-Based Gender Prediction in Uncontrolled Environments”. Duzce University Journal of Science and Technology 9 (2): 890-98. https://doi.org/10.29130/dubited.763427.

EndNote

Yıldız K, Güneş E, Bas A (April 1, 2021) CNN-based Gender Prediction in Uncontrolled Environments. Duzce University Journal of Science and Technology 9 2 890–898.

IEEE

[1]K. Yıldız, E. Güneş, and A. Bas, “CNN-based Gender Prediction in Uncontrolled Environments”, DUBİTED, vol. 9, no. 2, pp. 890–898, Apr. 2021, doi: 10.29130/dubited.763427.

ISNAD

Yıldız, Kazım - Güneş, Engin - Bas, Anil. “CNN-Based Gender Prediction in Uncontrolled Environments”. Duzce University Journal of Science and Technology 9/2 (April 1, 2021): 890-898. https://doi.org/10.29130/dubited.763427.

JAMA

1.Yıldız K, Güneş E, Bas A. CNN-based Gender Prediction in Uncontrolled Environments. DUBİTED. 2021;9:890–898.

MLA

Yıldız, Kazım, et al. “CNN-Based Gender Prediction in Uncontrolled Environments”. Duzce University Journal of Science and Technology, vol. 9, no. 2, Apr. 2021, pp. 890-8, doi:10.29130/dubited.763427.

Vancouver

1.Kazım Yıldız, Engin Güneş, Anil Bas. CNN-based Gender Prediction in Uncontrolled Environments. DUBİTED. 2021 Apr. 1;9(2):890-8. doi:10.29130/dubited.763427

CNN-based Gender Prediction in Uncontrolled Environments

CNN-based Gender Prediction in Uncontrolled Environments

Abstract

Keywords

Kontrolsüz Ortamlarda CNN Tabanlı Cinsiyet Tahmini

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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