Rabii Zahnoune

Skills: PySpark · Hadoop · Azure Data Factory · Microsoft Azure · SQL · Apache Airflow · Apache Kafka · Snowflake · Continuous Integration and Continuous Delivery (CI/CD) · Kubernetes · docker · Data Modeling

Project Overview: ExaFace is a web-based platform developed to enhance the security and integrity of exam processes by implementing real-time facial recognition. This application automates the verification of students' identities during exams, preventing fraud and ensuring fairness. Technologies Used: -Framework: Built using Django, a Python web framework, to handle the backend and facilitate efficient web development. -Deep Learning: Utilized TensorFlow, a powerful deep learning library, for processing and facial recognition tasks. -Facial Recognition Algorithm: Integrated FaceNet, an advanced deep learning model, to generate facial embeddings for precise identification. -Siamese Neural Network: Implemented a Siamese network architecture to compare live images with stored embeddings, ensuring high accuracy in student authentication. Key Features: -Real-time Authentication: The system captures live video or images of students and compares them against pre-registered data using facial embeddings. -Exam Integrity: By reducing manual identification errors and minimizing exam fraud, ExaFace provides a reliable solution for educational institutions. -Cross-Platform: Accessible on mobile and desktop devices, allowing exam proctors to easily authenticate students remotely.