Neural networks contribution in face mask detection to reduce the spread of COVID-19

Abstract

In front of COVID-19 propagation, we can protect our self by taking precautionary measures such as wearing face masks. It may be mandatory in particular public place although some persons ignore this rule. Several research in face mask detection area have emerged and most of studies are based on deep learning. In this paper, we present a method to detect whether person wear a mask or not to prevent the propagation of virus. The approach is based on combination of Pulse Couple Neural Network and Fully Connected Neural Network and the processing is divided in three steps: geometrical, feature extraction and decision. The geometrical module selects the Region of Interest for given image and the feature extraction module composed by Pulse Couple Neural Network extracts all pertinent information which will be used by the last module for decision. This decision module makes directly a decision in case of non-complex classification without neural network training overwise the Fully Connected Neural Network continues the treatment. The input image may be captured from video surveillance sequence, the system triggers a signal alarm once a person doesn’t wear face mask. Our proposed approach was tested with different datasets like Kaggle, AIZOO, Moxa3K, Real-World Masked Face Dataset, Medical Masks Dataset, Face Mask Dataset and the accuracy varies from 83.2% to 100% with minimum computation time.

YOLOv5-S2C2: An Improved Method of Mask Detection Based on Lightweight

“…Since the onset of the COVID-19 pandemic, there has been a heightened focus on the use of face masks [1]. These masks not only prevent respiratory infectious diseases such as COVID-19, avian influenza, and tuberculosis but also significantly enhance human health and safety by effectively blocking the inhalation of harmful particles in everyday situations where severe air pollution is present [2].…”

Improved CNN System for Face Mask Recognition

“…Deep learning demonstrated its effectiveness in detecting various object types for all of these applications. For the task of detecting the presence of masks, a lot of techniques have been developed from scratch [9,10], like the proposed model that will be introduced in these papers. Consequently, face and mask detection systems based on arti cial intelligence are growing in popularity now [11,12,13].…”