Open AccessMask Detection and Tracing System
Author(s) -
Sanket Shete,
Kiran Tingre,
Ajay Panchal,
Vaibhav Tapse,
Bhagyashri Vyas
Publication year - 2021
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit201556
Subject(s) - computer science , convolutional neural network , artificial intelligence , face (sociological concept) , face detection , object class detection , set (abstract data type) , pattern recognition (psychology) , economic shortage , computer vision , tracing , facial recognition system , task (project management) , social science , linguistics , philosophy , management , sociology , government (linguistics) , economics , programming language , operating system
Covid19 has given a new identity for wearing a mask. It is meaningful when these masked faces are detected accurately and efficiently. As a unique face detection task, face mask detection is much more difficult because of extreme occlusions which leads to the loss of face details. Besides, there is almost no existing large-scale accurately labelled masked face dataset, which increase the difficulty of face mask detection. The system encourages to use CNN-based deep learning algorithms which has done vast progress towards researches in face detection In this paper, we propose novel CNN-based method which is formed of three convolutional neural networks to detect face mask. Besides, because of the shortage of face masked training samples, we propose a new dataset called” face mask dataset” to finetune our CNN models. We evaluate our proposed face mask detection algorithm on the face mask testing set, and it achieves satisfactory performance