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JAIT 2023 Vol.14(1): 94-101
doi: 10.12720/jait.14.1.94-101

An Automated Deep Learning Framework for Human Identity and Gender Detection

Afaf Tareef, Hayat Al-Dmour*, and Afnan Al-Sarayreh
Faculty of Information Technology, Mutah University, Jordan
*Correspondence: hayatdmour@gmail.com

Manuscript received August 3, 2022; revised September 2, 2022; accepted September 30, 2022; published February 16, 2023.

Abstract—Automated detection of human identity and gender offers several industrial applications in near future, such as monitoring, surveillance, commercial profiling and human computer interaction. In this paper, deep learning techniques have been used to investigate the problem of human identity and gender classification using hand images. First, pre-processing techniques have been applied to enhance the appearance of the hand images. The pre-processed image is passed through the convolution neural network to determine the gander. For identity detection, the network has been trained on the images for the determined gender for better recognition. To further enhance the result, the framework has been implemented using different optimizers and k fold cross-validation.  Experimental results have shown that highly effective performance is achieved in both the human identification and gender classification objectives. High average accuracy of 97.75% using the dorsal hand side for human identification and 96.79% has been obtained for gender classification using the palm hand side. Conclusively, the proposed method has achieved more accuracy than the previous methods both for identification and gender classification.
Keywords—human identification, gender classification, deep learning
Cite: Afaf Tareef, Hayat Al-Dmour, and Afnan Al-Sarayreh, "An Automated Deep Learning Framework for Human Identity and Gender Detection," Journal of Advances in Information Technology, Vol. 14, No. 1, pp. 94-101, February 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.