Face Detection Algorithm for Security Application Using YOLOv7

Real-time face detection is becoming increasingly important in security applications, such as video surveillance and access control. This research implements YOLOv7, the latest algorithm in the YOLO family, to detect faces in complex environments . With its advanced architecture, YOLOv7 offers high speeds of up to 45 frames per second and an average precision (mAP) of 96.5%. Experiments were conducted under various conditions, including low lighting, crowded scenes, and partially occluded faces. The results show that YOLOv7 is highly suitable for enhancing the efficiency and reliability of AI-based security systems, making it a valuable tool for modern security solutions and applications.