Age and Gender Identification through Advanced Deep Learning Techniques

Authors

  • Md Serajun Nabi School of Computing and Informatics Albukhary International University Author
  • Zaidan Mufaddhal School of Computing and Informatics Albukhary International University Author
  • Lin Khant Khai School of Computing and Informatics Albukhary International University Author
  • Akibu Mahmoud Abdullahi School of Computing and Informatics Albukhary International University Author

DOI:

https://doi.org/10.53840/myjict8-2-36

Keywords:

gender detection, age detection, deep learning, facial features, bias and ethics

Abstract

The ability to automatically detect the gender and age of an individual based on their facial features or other attributes is an important task in computer vision and deep learning. The precision and dependability of gender and age detection models have significantly increased with the use of deep learning algorithms and massive datasets. The lack of diversity in the training data, which can result in prejudice and subpar performance on members of underrepresented groups, is only one of several issues that still need to be resolved. Deep learning for gender and age detection also poses ethical issues including the possibility of abuse and prejudice. The goal of this work is to overcome these difficulties and create models that are very accurate at identifying a person's gender and age. The study's objectives include incorporating ethical issues into the creation and use of the models as well as enhancing the models' effectiveness on members of underrepresented groups. The model will also be optimized for real-time uses in this study, including security and marketing.

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References

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Published

09-07-2024

Issue

Section

Articles

How to Cite

Age and Gender Identification through Advanced Deep Learning Techniques. (2024). Malaysian Journal of Information and Communication Technology (MyJICT), 8(2), 23-30. https://doi.org/10.53840/myjict8-2-36