A Comparative Study of Embedded Learning Models IoT-based for real time Mask Detection

Abstract

Following the outbreak of the coronavirus, many preventive measures are implemented to slow down the transmission of the virus. Amongst others, facemask detection is a key innovative technology that allows the identificationof the number of individuals wearing face masks. In this regard, this paperprovides a comparative study of several machine learning and deep learningalgorithms (e.g., SVM, RNN, Mask-RCNN, LSTM, CNN, Auto-Encoder,GAN, U-Net GAN) that support mask detection.