Improving video surveillance systems in banks using deep learning techniques
In the contemporary world, security and safety are signifcant concerns for any country that wants to succeed in tourism, attracting investors, and economics. Manually, guards monitoring 24/7 for robberies or crimes becomes an exhaustive task, and real-time response is essential and helpful for preve...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| منشور في: |
2023
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/2783 https://doi.org/10.1038/s41598-023-35190-9. |
| الوسوم: |
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| _version_ | 1862980611966238720 |
|---|---|
| author | Zahrawi, Mohammad |
| author2 | Shaalan, Khaled |
| author2_role | author |
| author_facet | Zahrawi, Mohammad Shaalan, Khaled |
| author_role | author |
| dc.creator.none.fl_str_mv | Zahrawi, Mohammad Shaalan, Khaled |
| dc.date.none.fl_str_mv | 2023 2025-02-10T05:26:32Z 2025-02-10T05:26:32Z |
| dc.identifier.none.fl_str_mv | Zahrawi, M. and Shaalan, K. (2023) “Improving video surveillance systems in banks using deep learning techniques,” Scientific Reports (Nature Publisher Group), 13(1), p. 7911. 2045-2322 https://bspace.buid.ac.ae/handle/1234/2783 https://doi.org/10.1038/s41598-023-35190-9. |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Proquest central |
| dc.relation.none.fl_str_mv | Scientific Reports (Nature Publisher Group)v13 n1 (2023): 7911 |
| dc.subject.none.fl_str_mv | Computational science Electrical and electronic engineering Information technology Software |
| dc.title.none.fl_str_mv | Improving video surveillance systems in banks using deep learning techniques |
| dc.type.none.fl_str_mv | Article |
| description | In the contemporary world, security and safety are signifcant concerns for any country that wants to succeed in tourism, attracting investors, and economics. Manually, guards monitoring 24/7 for robberies or crimes becomes an exhaustive task, and real-time response is essential and helpful for preventing armed robberies at banks, casinos, houses, and ATMs. This paper presents a study based on real-time object detection systems for weapons auto-detection in video surveillance systems. We propose an early weapon detection framework using state-of-the-art, real-time object detection systems such as YOLO and SSD (Single Shot Multi-Box Detector). In addition, we considered closely reducing the number of false alarms in order to employ the model in real-life applications. The model is suitable for indoor surveillance cameras in banks, supermarkets, malls, gas stations, and so forth. The model can be employed as a precautionary system to prevent robberies by implying the model in outdoor surveillance cameras. |
| id | budr_23de9995bfb1a94c749e460ee91558f8 |
| identifier_str_mv | Zahrawi, M. and Shaalan, K. (2023) “Improving video surveillance systems in banks using deep learning techniques,” Scientific Reports (Nature Publisher Group), 13(1), p. 7911. 2045-2322 |
| 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:1234/2783 |
| publishDate | 2023 |
| publisher.none.fl_str_mv | Proquest central |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Improving video surveillance systems in banks using deep learning techniquesZahrawi, MohammadShaalan, KhaledComputational science Electrical and electronic engineering Information technology SoftwareIn the contemporary world, security and safety are signifcant concerns for any country that wants to succeed in tourism, attracting investors, and economics. Manually, guards monitoring 24/7 for robberies or crimes becomes an exhaustive task, and real-time response is essential and helpful for preventing armed robberies at banks, casinos, houses, and ATMs. This paper presents a study based on real-time object detection systems for weapons auto-detection in video surveillance systems. We propose an early weapon detection framework using state-of-the-art, real-time object detection systems such as YOLO and SSD (Single Shot Multi-Box Detector). In addition, we considered closely reducing the number of false alarms in order to employ the model in real-life applications. The model is suitable for indoor surveillance cameras in banks, supermarkets, malls, gas stations, and so forth. The model can be employed as a precautionary system to prevent robberies by implying the model in outdoor surveillance cameras.Proquest central2025-02-10T05:26:32Z2025-02-10T05:26:32Z2023ArticleZahrawi, M. and Shaalan, K. (2023) “Improving video surveillance systems in banks using deep learning techniques,” Scientific Reports (Nature Publisher Group), 13(1), p. 7911.2045-2322https://bspace.buid.ac.ae/handle/1234/2783https://doi.org/10.1038/s41598-023-35190-9.enScientific Reports (Nature Publisher Group)v13 n1 (2023): 7911oai:bspace.buid.ac.ae:1234/27832026-01-29T15:02:33Z |
| spellingShingle | Improving video surveillance systems in banks using deep learning techniques Zahrawi, Mohammad Computational science Electrical and electronic engineering Information technology Software |
| title | Improving video surveillance systems in banks using deep learning techniques |
| title_full | Improving video surveillance systems in banks using deep learning techniques |
| title_fullStr | Improving video surveillance systems in banks using deep learning techniques |
| title_full_unstemmed | Improving video surveillance systems in banks using deep learning techniques |
| title_short | Improving video surveillance systems in banks using deep learning techniques |
| title_sort | Improving video surveillance systems in banks using deep learning techniques |
| topic | Computational science Electrical and electronic engineering Information technology Software |
| url | https://bspace.buid.ac.ae/handle/1234/2783 https://doi.org/10.1038/s41598-023-35190-9. |