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This project proposes an AI-powered face recognition system to combat exam impersonation in universities. The system leverages MATLAB, a powerful programming language for scientific and engineering computing, to achieve accurate and efficient facial identification during exams.

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Combating Exam Impersonation in Universities: An AI-powered Face Recognition System using MATLAB

Project Overview

This project proposes an AI-powered face recognition system to combat exam impersonation in universities. The system leverages MATLAB, a powerful programming language for scientific and engineering computing, to achieve accurate and efficient facial identification during exams.

Project Purpose

Exam impersonation is a growing concern in universities, jeopardising the integrity of academic evaluations. This project aims to develop a robust and reliable system to prevent impersonation, ensuring fairness and credibility in the examination process.

Key Features

  • Real-time face recognition: The system uses a webcam to capture student images during exams and compares them against a pre-registered database of authorised examinees.
  • AI-powered algorithms: Advanced machine learning algorithms trained on facial recognition datasets ensure accurate identification, even in challenging lighting or disguise conditions.
  • MATLAB integration: MATLAB provides a robust and versatile platform for developing and implementing the face recognition system, offering flexibility and scalability.
  • Secure data management: The system prioritizes data privacy and security, implementing measures to protect student information and prevent unauthorized access.

Benefits and Impact

This AI-powered face recognition system offers several benefits, including:

  • Enhanced exam security: Reduces the risk of impersonation and safeguards the integrity of academic evaluations.
  • Fairness and equality: Ensures that all students are assessed based on their own merit and abilities.
  • Improved student experience: Creates a more secure and trustworthy examination environment for students.
  • Streamlined exam administration: Automates the identification process, saving time and resources for exam administrators.

Conclusion

This project presents a promising solution to address the growing challenge of exam impersonation in universities. By leveraging the power of AI and MATLAB, the system offers a secure, efficient, and reliable approach to ensure the fairness and credibility of academic assessments.

Requirements

  • MATLAB: ≥R2018a
  • caffee: Deep Learning library for MATLAB
  • toolbox-master

Pipeline

Face Verification procees Face Verification process

Face Recognition process Face Recognition process


GUI Screenshots


Notes

  • Double check path in code to run

About

This project proposes an AI-powered face recognition system to combat exam impersonation in universities. The system leverages MATLAB, a powerful programming language for scientific and engineering computing, to achieve accurate and efficient facial identification during exams.

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