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Deep Learning Based Facial Mask Detection Using Mobilenetv2

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Computational Intelligence in Pattern Recognition (CIPR 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 480))

Abstract

The Covid-19 pandemic has had a profound effect on our daily lives. One of the most effective ways to protect ourselves from this virus is to wear face masks. This research paper introduces face mask detection that authorities can use to reduce and prevent COVID-19. The face mask recognition process in this research paper is done with a deep learning algorithm and image processing done using MobileNetV2. Steps to build the model are data collection, pre-processing, data classification, model training and model testing. The authors came up with this approach due to the recent Covid-19 situations for following specific guidelines and the uprising trend of Artificial Intelligence and Machine Learning and its real-world practices. This system has been made to detect more than one person whether they are wearing masks or not. This system also gives us the Covid cases-related worldwide updates as per our chosen country and type of cases like total cases, total deaths etc. Such systems are already available, but the efficiency of the available mask detection systems was not achieved thoroughly. This newly developed system proposes to take a step further, which recognizes more than one person at a time and increases the accuracy level to a much greater extent.

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Authors and Affiliations

  1. Computer Science Engineering Department, University of Engineering and Management, Kolkata, Kolkata, India

    Arijit Goswami

  2. Computer Science Information Technology Engineering Department, University of Engineering and Management, Kolkata, Kolkata, India

    Biswarup Bhattacharjee, Rahul Debnath, Ankita Sikder & Sudipta Basu Pal

Authors
  1. Arijit Goswami
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  2. Biswarup Bhattacharjee
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  3. Rahul Debnath
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  4. Ankita Sikder
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  5. Sudipta Basu Pal
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Corresponding author

Correspondence to Sudipta Basu Pal .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, West Bengal, India

    Asit Kumar Das

  2. P. G. Department of Computer Science, Maharaja Sriram Chandra Bhanja Deo (MSCB) University, Baripada, Mayurbhanj, Odisha, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Department of Artificial Intelligence and Data Science, Ramco Institute of Technology, Rajapalayam, Tamil Nadu, India

    S. Vimal

  5. Communication Sciences, University of Teramo, Teramo, Italy

    Danilo Pelusi

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The authors declare that they have no known competing monetary interests or personal relationships that could have appeared to influence the work reported in this paper.

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Goswami, A., Bhattacharjee, B., Debnath, R., Sikder, A., Basu Pal, S. (2022). Deep Learning Based Facial Mask Detection Using Mobilenetv2. In: Das, A.K., Nayak, J., Naik, B., Vimal, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. CIPR 2022. Lecture Notes in Networks and Systems, vol 480. Springer, Singapore. https://doi.org/10.1007/978-981-19-3089-8_8

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