Masked Face Recognition

• Tech Stack: Python, Tensorflow, OpenCv, Numpy
• Paper Link: Dergi Park

Developed a Face Recognition Program for Masked Individuals
Pioneered the development of a cutting-edge face recognition system designed to identify individuals even when wearing masks. The program was specifically created to enhance security measures while adhering to health guidelines, preventing the need for mask removal during identification.

Overcame Data Shortage Challenges through AI Simulation
Tackled the challenge of data shortage by leveraging artificial intelligence to simulate masked faces. This innovative solution enriched the dataset, enabling the system to train more effectively and achieve high levels of accuracy even when identifying individuals wearing masks.

Leveraged Computer Vision and AI Technologies
Utilized state-of-the-art computer vision and artificial intelligence algorithms to achieve highly accurate facial recognition. This technological backbone ensures the system's reliability and effectiveness in various environmental conditions and scenarios.

Achieved Exceptional Accuracy
Rigorously tested the program under different conditions to ensure optimal performance. Successfully achieved an accuracy rate of above 96.5%, demonstrating the system's robustness and reliability in real-world applications.

Health and Safety Applications
Aimed to contribute to public health efforts, the system allows for secure identification procedures without requiring mask removal, thereby reducing the risk of virus transmission. This feature makes the program particularly useful in sensitive areas such as healthcare facilities, airports, and other high-traffic public spaces.