Developing a Framework for Weapon and Mask Detection in Surveillance Systems

Financial institutions, jewelry stores, hypermarkets and automated teller machines all experience yearly thefts of vast amount of money. Police have dismantled a few of the robbery attempts. Police successfully apprehend most of the robbers. The maintenance of safety and security around the globe is...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: ZAHRAWI, MOHAMMAD HUSNI (author)
منشور في: 2022
الموضوعات:
الوصول للمادة أونلاين:https://bspace.buid.ac.ae/handle/1234/2128
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author ZAHRAWI, MOHAMMAD HUSNI
author_facet ZAHRAWI, MOHAMMAD HUSNI
author_role author
dc.creator.none.fl_str_mv ZAHRAWI, MOHAMMAD HUSNI
dc.date.none.fl_str_mv 2022-11
2023-01-06T07:03:51Z
2023-01-06T07:03:51Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 20209704
https://bspace.buid.ac.ae/handle/1234/2128
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv The British University in Dubai (BUiD)
dc.subject.none.fl_str_mv Artificial Intelligence (AI)
deep learning
computer vision
object detection
gun detection
YOLO
weapon detection
surveillance systems
mask detection
United Arab Emirates (UAE)
YOLO
dc.title.none.fl_str_mv Developing a Framework for Weapon and Mask Detection in Surveillance Systems
dc.type.none.fl_str_mv Dissertation
description Financial institutions, jewelry stores, hypermarkets and automated teller machines all experience yearly thefts of vast amount of money. Police have dismantled a few of the robbery attempts. Police successfully apprehend most of the robbers. The maintenance of safety and security around the globe is a difficult task for governments, particularly in a country like the UAE, which is home to more than 200 nationalities. This study examines the applications of neural network models in video surveillance systems for detecting weapons, thus preventing robberies. By expanding the dataset to include more classes and photos per class, the proposed model could perform better to be installed on outdoor surveillance systems. In this study, we will examine situations of weapons detectors, develop models using transfer learning approaches, and contrast them with other contemporary detectors like YOLOv5. We will develop our own unique dataset and contrast it with another dataset in terms of classes, image quality, and kind of items used for committing a robbery. Gun detectors in surveillance systems has a wide range of additional uses, from residentials units to the military.
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oai_identifier_str oai:bspace.buid.ac.ae:1234/2128
publishDate 2022
publisher.none.fl_str_mv The British University in Dubai (BUiD)
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spelling Developing a Framework for Weapon and Mask Detection in Surveillance SystemsZAHRAWI, MOHAMMAD HUSNIArtificial Intelligence (AI)deep learningcomputer visionobject detectiongun detectionYOLOweapon detectionsurveillance systemsmask detectionUnited Arab Emirates (UAE)YOLOFinancial institutions, jewelry stores, hypermarkets and automated teller machines all experience yearly thefts of vast amount of money. Police have dismantled a few of the robbery attempts. Police successfully apprehend most of the robbers. The maintenance of safety and security around the globe is a difficult task for governments, particularly in a country like the UAE, which is home to more than 200 nationalities. This study examines the applications of neural network models in video surveillance systems for detecting weapons, thus preventing robberies. By expanding the dataset to include more classes and photos per class, the proposed model could perform better to be installed on outdoor surveillance systems. In this study, we will examine situations of weapons detectors, develop models using transfer learning approaches, and contrast them with other contemporary detectors like YOLOv5. We will develop our own unique dataset and contrast it with another dataset in terms of classes, image quality, and kind of items used for committing a robbery. Gun detectors in surveillance systems has a wide range of additional uses, from residentials units to the military.The British University in Dubai (BUiD)2023-01-06T07:03:51Z2023-01-06T07:03:51Z2022-11Dissertationapplication/pdf20209704https://bspace.buid.ac.ae/handle/1234/2128enoai:bspace.buid.ac.ae:1234/21282023-01-06T23:00:23Z
spellingShingle Developing a Framework for Weapon and Mask Detection in Surveillance Systems
ZAHRAWI, MOHAMMAD HUSNI
Artificial Intelligence (AI)
deep learning
computer vision
object detection
gun detection
YOLO
weapon detection
surveillance systems
mask detection
United Arab Emirates (UAE)
YOLO
title Developing a Framework for Weapon and Mask Detection in Surveillance Systems
title_full Developing a Framework for Weapon and Mask Detection in Surveillance Systems
title_fullStr Developing a Framework for Weapon and Mask Detection in Surveillance Systems
title_full_unstemmed Developing a Framework for Weapon and Mask Detection in Surveillance Systems
title_short Developing a Framework for Weapon and Mask Detection in Surveillance Systems
title_sort Developing a Framework for Weapon and Mask Detection in Surveillance Systems
topic Artificial Intelligence (AI)
deep learning
computer vision
object detection
gun detection
YOLO
weapon detection
surveillance systems
mask detection
United Arab Emirates (UAE)
YOLO
url https://bspace.buid.ac.ae/handle/1234/2128