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  • Open Access


    Deep Learning Based Face Mask Detection in Religious Mass Gathering During COVID-19 Pandemic

    Abdullah S. AL-Malaise AL-Ghamdi1,2,3, Sultanah M. Alshammari3,4, Mahmoud Ragab3,5,6,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1863-1877, 2023, DOI:10.32604/csse.2023.035869

    Abstract Notwithstanding the religious intention of billions of devotees, the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most attendees ignored preventive measures, namely maintaining physical distance, practising hand hygiene, and wearing facemasks. Wearing a face mask in public areas protects people from spreading COVID-19. Artificial intelligence (AI) based on deep learning (DL) and machine learning (ML) could assist in fighting covid-19 in several ways. This study introduces a new deep learning-based Face Mask Detection in Religious Mass… More >

  • Open Access


    Human Faces Detection and Tracking for Crowd Management in Hajj and Umrah

    Riad Alharbey1, Ameen Banjar1, Yahia Said2,3,*, Mohamed Atri4, Abdulrahman Alshdadi1, Mohamed Abid5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6275-6291, 2022, DOI:10.32604/cmc.2022.024272

    Abstract Hajj and Umrah are two main religious duties for Muslims. To help faithfuls to perform their religious duties comfortably in overcrowded areas, a crowd management system is a must to control the entering and exiting for each place. Since the number of people is very high, an intelligent crowd management system can be developed to reduce human effort and accelerate the management process. In this work, we propose a crowd management process based on detecting, tracking, and counting human faces using Artificial Intelligence techniques. Human detection and counting will be performed to calculate the number… More >

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