Deep learning-based face recognition using conventional feature extraction methods

This study aims to enhance facial recognition performance by combining traditional feature extraction methods with deep learning techniques. The goal is to develop a more precise and reliable facial recognition system by leveraging the information obtained from traditional methods alongside the learning capabilities of deep learning algorithms. The results will be used to measure and evaluate the performance improvements arising from the combination of deep learning and traditional feature extraction approaches. These findings are expected to contribute to technological advancements in various application areas such as security, automation, human-machine interaction, and more.