Open AccessComparative analysis of CNN and Viola-Jones for face mask detection
Author(s) -
M. Sivakumar,
N. Saranprasath,
N. S. Sridharan,
V. Praveen
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1916/1/012043
Subject(s) - computer science , artificial intelligence , convolutional neural network , face (sociological concept) , deep learning , face detection , lock (firearm) , covid-19 , pandemic , face masks , field (mathematics) , artificial neural network , computer vision , viola , viola–jones object detection framework , pattern recognition (psychology) , facial recognition system , geography , history , mathematics , medicine , sociology , infectious disease (medical specialty) , social science , archaeology , pathology , disease , pure mathematics , piano , art history
According to the World Health Organization, the Coronavirus (COVID-19) pandemic is causing a worldwide emergency, and one safe way to cover oneself is to wear masks. This pandemic constrained governments everywhere in the world to force lock-downs to avoid the transmission of infection. Reports show that wearing masks at work diminishes the danger of infection. We assemble our model by utilizing the concept of deep neural learning and AI. The dataset comprises pictures with masked faces and non-masked faces. Several computer algorithms are there for face detection. But this analysis centers around two of the most widely recognized procedures: The Viola-Jones algorithm and the Convolution Neural Networks. We will check whether the individual in the image/video wears a mask or not with a CV and Deep neural learning. Not only finding out about face mask detection, but this project also introduced the chance to delve into the field of computer algorithms.