Survey towards Mask Detection and Tracing

Authors

  • Sanket Shete  Department of Computer Engineering, Dr. D. Y. Patil School of Engineering and Technology, Pune, Maharashtra, India
  • Kiran Tingre  Department of Computer Engineering, Dr. D. Y. Patil School of Engineering and Technology, Pune, Maharashtra, India
  • Ajay Panchal  Department of Computer Engineering, Dr. D. Y. Patil School of Engineering and Technology, Pune, Maharashtra, India
  • Vaibhav Tapse  Department of Computer Engineering, Dr. D. Y. Patil School of Engineering and Technology, Pune, Maharashtra, India
  • Prof. Bhagyashree Dhakulkar  Department of Computer Engineering, Dr. D. Y. Patil School of Engineering and Technology, Pune, Maharashtra, India

Keywords:

Face mask, CNN, Face detection, Deep learning

Abstract

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

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International Journal of Scientific Research in Science and Technology

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Published

2021-02-28

Issue

Volume 8, Issue 1, January-February-2021

Section

Research Articles

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Copyright (c) IJSRST

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sanket Shete, Kiran Tingre, Ajay Panchal, Vaibhav Tapse, Prof. Bhagyashree Dhakulkar "Survey towards Mask Detection and Tracing" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 1, pp.129-133, January-February-2021.