Deep Learning Model Based on Mobile-Net with Haar like Algorithm for Masked Face Recognition at Nuclear Facilities

During the spread of COVID-I9 pandemic in early 2020, WHO organization advised all people world to wear face-mask limit COVID-19. Many facilities required that their employees face-mask. For safety facility, it was mandatory recognize identity individual wearing mask. Hence, face recognition masked individuals required. In this research, a novel technique is proposed based on mobile-net and Haar-like algorithm for detecting recognizing face. Firstly, authorized person enters nuclear facility case masked-face using mobile-net. Secondly, applying features detect retina extract boundary box around compares with dataset without mask recognition. The results modal, which tested from Kaggle, yielded 0.99 accuracies, loss 0.08, F1.score 0.98.