THESIS TITLE HUMAN FACE RECOGNITION AND ANALYSIS WITHOUT FACEMASK

Abstract

Everybody is encouraged to wear a face mask during coronavirus outbreaks to prevent the spread of the COVID19 virus effectively. However, there are no public masked face recognition prototypes to help all people detect someone wearing a mask when joining society such as in factories, companies, schools, etc. This makes current facial recognition technology in many cases unsuccessful. Therefore, this paper, based on secondary research, discusses mask detection enhancing identification quality on masked faces from current face recognition technologies, describing which dataset, library, methodology, and algorithm was used to develop the project. All in all, the paper concludes that the purpose of this application is for the health of the community, contributing to the difficult situation of the world today, to repel the epidemic quickly