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

Amal Algefes; Nouf Aldossari; Fatma Masmoudi

doi:10.1007/978-981-19-2394-4_55

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

Amal Algefes
, Nouf Aldossari
, Fatma Masmoudi

Information Systems

Prince Sattam Bin Abdulaziz University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022
Editors	Xin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	601-609
Number of pages	9
ISBN (Print)	9789811923937
DOIs	https://doi.org/10.1007/978-981-19-2394-4_55
State	Published - 2023
Event	7th International Congress on Information and Communication Technology, ICICT 2022 - Virtual, Online Duration: 21 Feb 2022 → 24 Feb 2022

Publication series

Name	Lecture Notes in Networks and Systems
Volume	464
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	7th International Congress on Information and Communication Technology, ICICT 2022
City	Virtual, Online
Period	21/02/22 → 24/02/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

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

Access to Document

10.1007/978-981-19-2394-4_55

Cite this

Algefes, A., Aldossari, N., & Masmoudi, F. (2023). Image Recognition to Detect COVID-19 Violations: Saudi Arabia Use Case. In X.-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022 (pp. 601-609). (Lecture Notes in Networks and Systems; Vol. 464). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-2394-4_55

Algefes, Amal ; Aldossari, Nouf ; Masmoudi, Fatma. / Image Recognition to Detect COVID-19 Violations : Saudi Arabia Use Case. Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022. editor / Xin-She Yang ; Simon Sherratt ; Nilanjan Dey ; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2023. pp. 601-609 (Lecture Notes in Networks and Systems).

@inproceedings{7690af4df3e84f1ab14307a708f1dfe1,

title = "Image Recognition to Detect COVID-19 Violations: Saudi Arabia Use Case",

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.",

keywords = "COVID-19, Deep learning, Image classification, ResNet, Violation and non-violation",

author = "Amal Algefes and Nouf Aldossari and Fatma Masmoudi",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 7th International Congress on Information and Communication Technology, ICICT 2022 ; Conference date: 21-02-2022 Through 24-02-2022",

year = "2023",

doi = "10.1007/978-981-19-2394-4\_55",

language = "English",

isbn = "9789811923937",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "601--609",

editor = "Xin-She Yang and Simon Sherratt and Nilanjan Dey and Amit Joshi",

booktitle = "Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022",

address = "Germany",

}

Algefes, A, Aldossari, N & Masmoudi, F 2023, Image Recognition to Detect COVID-19 Violations: Saudi Arabia Use Case. in X-S Yang, S Sherratt, N Dey & A Joshi (eds), Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022. Lecture Notes in Networks and Systems, vol. 464, Springer Science and Business Media Deutschland GmbH, pp. 601-609, 7th International Congress on Information and Communication Technology, ICICT 2022, Virtual, Online, 21/02/22. https://doi.org/10.1007/978-981-19-2394-4_55

Image Recognition to Detect COVID-19 Violations: Saudi Arabia Use Case. / Algefes, Amal; Aldossari, Nouf; Masmoudi, Fatma.
Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022. ed. / Xin-She Yang; Simon Sherratt; Nilanjan Dey; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2023. p. 601-609 (Lecture Notes in Networks and Systems; Vol. 464).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Image Recognition to Detect COVID-19 Violations

T2 - 7th International Congress on Information and Communication Technology, ICICT 2022

AU - Algefes, Amal

AU - Aldossari, Nouf

AU - Masmoudi, Fatma

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - COVID-19

KW - Deep learning

KW - Image classification

KW - ResNet

KW - Violation and non-violation

UR - https://www.scopus.com/pages/publications/85135042966

U2 - 10.1007/978-981-19-2394-4_55

DO - 10.1007/978-981-19-2394-4_55

M3 - Conference contribution

AN - SCOPUS:85135042966

SN - 9789811923937

T3 - Lecture Notes in Networks and Systems

SP - 601

EP - 609

BT - Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022

A2 - Yang, Xin-She

A2 - Sherratt, Simon

A2 - Dey, Nilanjan

A2 - Joshi, Amit

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 21 February 2022 through 24 February 2022

ER -

Algefes A, Aldossari N, Masmoudi F. Image Recognition to Detect COVID-19 Violations: Saudi Arabia Use Case. In Yang XS, Sherratt S, Dey N, Joshi A, editors, Proceedings of 7th International Congress on Information and Communication Technology, ICICT 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 601-609. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-19-2394-4_55

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this