Face Mask Detection In The Covid-19 Pandemic Era by Implementing Convolutional Neural Network and Pre-Trained CNN Models
Ivana Lucia Kharisma, Rahmadya Trias Handayanto, Deshinta Arrova Dewi · 2021
The Coronavirus or Covid-19 has spread widely throughout the world since the beginning of 2020. WHO provides basic guidance in preventing the spread of the virus that can be done by the community. One of them is the use of masks when doing activities outside the home. Lack of awareness in mask usage become the obstacle in the process of efforts to prevent the spread of covid 19. The aim of this research is to develop a face mask detection model by implementing the convolutional neural network and pre trained CNN algorithm. The accuracy of the proposed models in training process, the accuracy of CNN, VGG16, and VGG19 are 97.79%, 99.87% and 100%, respectively. The proposed models evaluated using confusion matrix using testing datasets given.