Image Recognition to Detect COVID-19 Violations: Saudi Arabia Use Case

Amal Algefes, Nouf Aldossari, Fatma Masmoudi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The upsurge in the number of criminal cases in Saudi Arabia is a cause for concern. More so, with the recent emergence of COVID-19, the government has forbidden specific social behaviors, which means that any breach of these prohibitions will be classified as a criminal. This work leverages the immense ability of deep learning architectures to develop and evaluate models to detect images of people or a person either violating or observing COVID-19 rules. For instance, an image of a person/s wearing a face mask would definitely fall under the category of non-violation, whereas an image of people hugging or shaking hands is an indication of a violation of COVID-19 rules. The model is trained and evaluated on a bunch of images that we have extracted from social media sites, and it produces exceptional results in the image classification assignment that we have performed.

Original languageEnglish
Title of host publicationProceedings of 7th International Congress on Information and Communication Technology, ICICT 2022
EditorsXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages601-609
Number of pages9
ISBN (Print)9789811923937
DOIs
StatePublished - 2023
Event7th International Congress on Information and Communication Technology, ICICT 2022 - Virtual, Online
Duration: 21 Feb 202224 Feb 2022

Publication series

NameLecture Notes in Networks and Systems
Volume464
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference7th International Congress on Information and Communication Technology, ICICT 2022
CityVirtual, Online
Period21/02/2224/02/22

Keywords

  • COVID-19
  • Deep learning
  • Image classification
  • ResNet
  • Violation and non-violation

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