Open AccessCOVID-19 Face Mask Detection
Author(s) -
Prof. Kalpana Malpe
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40005
Subject(s) - artificial intelligence , face (sociological concept) , computer science , convolutional neural network , computer vision , pattern recognition (psychology) , identification (biology) , face masks , face detection , object class detection , covid-19 , facial recognition system , medicine , social science , botany , disease , pathology , sociology , infectious disease (medical specialty) , biology
Face mask detection involves in detection the placement of the face then crucial whether or not it's a mask thereon or not. the problem is proximately cognate to general object notion to detect the categories of objects. Face identification flatly deals with identifying a particular cluster of entities i.e., Face. it's varied applications, like autonomous driving, education, police work, and so on. This paper presents a simplified approach to serve the above purpose using the basic Machine Learning (ML) packages such as TensorFlow, Keras, OpenCV and Scikit-Learn. The planned technique detects the face from the image properly and so identifies if it's a mask on that or not. As an investigation taskperforming artist, it ought to conjointly sight a face at the side of a mask in motion. The technique perform accuracyup to 95.77% and 94.58% respectively on two different datasets and count optimized values of parameters using the Sequential Convolutional Neural Network model to detect the presence of masks correctly without causing over-fitting. Keywords: TensorFlow, Keras, OpenCV and Scikit- Learn