Developed an Artificial Intelligence model for face recognition that can detect and identify human faces from images or video streams. The system uses computer vision and machine learning techniques to analyze facial features and match them with stored identities.
The model first performs face detection to locate faces in an image, then extracts unique facial features to create a face embedding. These embeddings are compared with a database to determine the person's identity.
The project demonstrates the application of deep learning, image processing, and pattern recognition to build an intelligent system capable of recognizing individuals with high accuracy.
This system can be applied in areas such as security systems, attendance tracking, identity verification, and smart surveillance.