Human Age Prediction Based on Facial Patterns Using CNN

Authors

https://doi.org/10.48314/ceti.v1i2.30

Abstract

Deep learning has established its dominance and proved to be a powerful tool for increased accuracy and the ability to handle and process big data. One such popular Deep Neural Networks (DNN) is Convolutional Neural Network (CNN), a class of deep NN, applied to analyze and predict visual imagery. In this paper age estimation problem is adressed. Advancement in technology has increased the expectation of consumers. Face detection and age prediction are the two top technological trends on social media platforms. The trained model attempts to identify an image and then predict its age using deep learning models. We have used CNN algorithm for the final model after the effort was made in selecting the most efficient algorithms among RNN and GAN. The model is trained using different age classifiers and results obtained showed improvement in the performance of age estimation.

Keywords:

Convolutional neural networks, Deep learning, Machine learning, Age estimation

References

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Published

2024-06-17

Issue

Vol. 1 No. 2 (2024): Computational Engineering and Technology Innovations

Section

Articles

How to Cite

Safa, R., Petrovic, N., Nozick, V., & Cevallos-Torres, L. (2024). Human Age Prediction Based on Facial Patterns Using CNN. Computational Engineering and Technology Innovations, 1(2), 86-97. https://doi.org/10.48314/ceti.v1i2.30

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