@article {10.3844/jcssp.2024.1559.1568,
article_type = {journal},
title = {Facial Recognition and Discovery Using Convolution Deep Learning Neural Network},
author = {Baareh, Abdel Karim Mohamed},
volume = {20},
number = {11},
year = {2024},
month = {Oct},
pages = {1559-1568},
doi = {10.3844/jcssp.2024.1559.1568},
url = {https://thescipub.com/abstract/jcssp.2024.1559.1568},
abstract = {Facial recognition is a critical and well-established topic that has caught the interest of researchers across various application areas. Face detection and identification are critical components of human detection systems. Researchers in different fields used numerous techniques to recognize human faces in various positions considering several features, many results were also obtained. In this research, we aim to use a well-known method called a Deep Learning lightweight Convolutional Neural Network (CNN) for image recognition and detection techniques to contribute to solving the facial recognition problem. We used 280 FEI face images to recognize images of twenty persons from fourteen unique classes. Training and testing samples were considered. The proposed CNN model consists of only 16 layers, making it more portable and reliable for real-world applications. CNN shows outstanding performance, completing a training accuracy result of 97.73% and a testing accuracy result of 83.33%.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}