Futuristic Authentication: Development of an Artificial Intelligence based Enhanced Face Detection and Recognition System

This research presents the design and implementation of an advanced Face Detection and Recognition System employing an Artificial Intelligence Assisted Face Recognition Model (AIFRM). The proposed system leverages the powerful Cascaded VGG16 architecture to enhance the accuracy of face detection and recognition tasks. The methodology involves a two-step approach, beginning with robust face detection using the cascaded VGG16 model. This is followed by feature extraction and recognition using the same architecture, resulting in a highly efficient and accurate facial recognition system. The cascaded VGG16 model is trained on diverse datasets to ensure adaptability to various scenarios and lighting conditions, enhancing the system's real-world applicability. The experimental results demonstrate the effectiveness of the proposed system in achieving state-of-the-art accuracy in face detection and recognition. The cascaded VGG16 model proves to be a formidable backbone for the AIFRM, contributing to the system's success in handling complex scenarios. The system's high accuracy, reaching 97%, positions it as a reliable solution for security, surveillance, and authentication applications in diverse environments.