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Search Results for you-only-look-once-yolo-

Article
Improving Facial Identification System Based on YOLOv8 Deep Learning Algorithm

Huda S. Mithkhal, Ahmed H Y Al-Noori, Emad Tariq Al-Shiekhly

Pages: 351-356

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Abstract

In recent years, the interest in biometric identification systems has increased, due to the worry about security matters in the world.  Face recognition technique is one type of biometric identification technology and is considered the most widely employed .it represents one of the most significant pattern recognition technologies that use characteristics included in facial images or videos to detect the identity of individuals. Recently, it has become more important as it is used in many security applications. In recent years, Most of the traditional facial identification algorithms have faced limitations in identification and verification accuracy. As a result, this work presents a sophisticated system for face identification adopting a novel algorithm of deep learning: You Only Look Once version 8 (YOLOv8). This algorithm can detect the face identity of different individuals with different positions with high accuracy. The face identification technique consists of four main phases which are the image acquisition phase, preprocessing phase, features extraction phase, and classification phase. The YOLOv8 model has been trained for head pose images (HPI) datasets consisting of 1700 images divided as training, validation, and test images of 1190, 255, and 255, respectively. The experimental results show proposed algorithm achieved a significant improvement in face identification accuracy of 99% of mean average precision in which outperforms many state-of-the-art face identification techniques. 

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