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...
محفوظ في:
| المؤلف الرئيسي: | |
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| منشور في: |
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/2128 |
| الوسوم: |
إضافة وسم
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| _version_ | 1862980618037493760 |
|---|---|
| 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. |
| id | budr_50c51827eef4de06b4482fbb33572c2b |
| identifier_str_mv | 20209704 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/2128 |
| publishDate | 2022 |
| publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| 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 |