Partial Facial Identification using Transfer Learning Technique

Abstract

In today’s world, people go outside wearing a face mask, so face detection and face recognition models need to take this into account. Facial recognition has been researched widely with various algorithms. Since the coronavirus disease of 2019 (COVID-19) outbreak has spread across Thailand, our use of face recognition models has reminded people to wear a face mask. This is because when people go outside, they are likely to be exposed to facial image detection and classification methods which are used for authentication and authorization. In this paper, we use transfer learning such as YOLOv3 and training with public datasets and donation datasets. Our models can recognize faces with a 98.7% accuracy rate and identify faces including those with face masks-with a 92.7% accuracy rate.