Real-world human gender classification from oral region using convolutional neural netwrok

Mohamed Oulad-Kaddour; Hamid Haddadou; Cristina Conde; Daniel Palacios-Alonso; Enrique Cabello

doi:10.14201/adcaij.27797

Real-world human gender classification from oral region using convolutional neural netwrok

Mohamed Oulad-Kaddour

Ecole naionale Supéerieure en Informatique m_ouled_kaddour[at]esi.dz
Hamid Haddadou

Ecole naionale Supéerieure en Informatique
Cristina Conde

Rey Juan Carlos University
Daniel Palacios-Alonso

Rey Juan Carlos University
Enrique Cabello

Rey Juan Carlos University

https://doi.org/10.14201/adcaij.27797

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How to Cite

Oulad-Kaddour, M., Haddadou, H., Conde, C., Palacios-Alonso, D., & Cabello, E. (2023). Real-world human gender classification from oral region using convolutional neural netwrok . ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 11(3), 249–261. https://doi.org/10.14201/adcaij.27797

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Editorial dates

Submitted:

22-11-2021

Acceptance:

16-03-2022

Published:

24-01-2023

Issue

Vol. 11 No. 3 (2022)

Section

Articles

Keywords

gender classification
face biometrics
oral region biometrics
convolutional neural networks
deep learning

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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