NeuralFace

NeuralFace is a cutting-edge mobile application that leverages advanced deep learning techniques for real-time facial recognition and identity verification. Built using Flutter for cross-platform compatibility and TensorFlow Lite for efficient on-device inference, this project demonstrates the practical implementation of AI in mobile security applications.

The application utilizes Google's ML Kit for face detection and recognition, combined with custom-trained neural networks optimized for mobile deployment. The system can accurately identify individuals in various lighting conditions and facial orientations, making it suitable for security and access control applications.

One of the key innovations of NeuralFace is its edge computing approach, where all face recognition processing happens locally on the device, ensuring privacy and reducing latency. The app includes features like liveness detection to prevent spoofing attacks and supports multiple face enrollment for comprehensive identity management.

The project showcases modern mobile AI development practices, including model quantization for efficient inference, secure biometric data handling, and intuitive user interface design that makes advanced AI technology accessible to end users.