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Deep learning for face mask detection: a survey.

Aanchal Sharma1, Rahul Gautam1, Jaspal Singh1

  • 1Department of Computer Science & Engineering, Sant Longowal Institute of Engineering & Technology, Longowal, Punjab India.

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Summary
This summary is machine-generated.

This review examines face mask detection systems using artificial intelligence to help curb COVID-19 transmission. It analyzes various datasets, techniques, and performance metrics for object detection in the context of the pandemic.

Keywords:
COVID-19Convolutional neural networkDeep learningFace mask detectionMachine learningObject detection

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Area of Science:

  • Computer Vision
  • Image Processing
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning

Background:

  • The COVID-19 pandemic, declared by the World Health Organization (WHO) in March 2020, has had a profound global impact, with over 220 million cases and 4.56 million deaths by September 2021.
  • Despite widespread vaccine administration, global vaccination rates remain insufficient to fully contain the virus.
  • WHO recommends mask usage as a critical measure to restrain virus transmission, necessitating effective face mask detection systems.

Purpose of the Study:

  • To review existing research on face mask detection systems.
  • To analyze datasets, techniques, and performance metrics used in face mask detection.
  • To identify trends, patterns, limitations, and areas for improvement in the field.

Main Methods:

  • Object detection, encompassing image classification and localization, is the core technology for face mask detection.
  • Deep learning, a subset of machine learning and artificial intelligence, is widely employed.
  • Hybrid approaches are also utilized to enhance the efficiency of face mask detection systems.

Main Results:

  • The paper reviews various research studies on face mask detection.
  • It details the datasets and techniques employed in these studies.
  • Performance metrics, limitations, and potential improvements are discussed.

Conclusions:

  • Face mask detection is a crucial application of computer vision and deep learning in the context of the COVID-19 pandemic.
  • This review provides a comprehensive overview for researchers to understand current trends and identify future research directions.
  • Further research is needed to address limitations and enhance the performance of face mask detection systems.