Citation
Mohamad, Muhammad Ekmal Eiman Quyyum and Lye, Haris and Ahmad Fauzi, Mohammad Faizal (2022) Weapon Detection In Surveillance Videos Using Deep Neural Networks. Periodic Research Publication, Faculty of Engineering. (Unpublished)
Text
23_1171102157_Muhammad Ekmal_Haris_ FYP2 Poster.pdf Restricted to Repository staff only Download (1MB) |
Abstract
Many cases regarding dangerous weapon is increasing in society such as robbery mass shooting and terrorism which can jeopardize the safety of people. One of the cases in New Zealand involved 49 people were killed in two anti Muslim terrorist attack. Cases in Malaysia such as robbery incident in shopping mall occurred due to lack of security system. Therefore, implementation of weapon detection in surveillance camera (CCTV) can improve security level.
Item Type: | Other |
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Uncontrolled Keywords: | Deep Neural Networks |
Subjects: | Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software |
Divisions: | Faculty of Engineering (FOE) |
Depositing User: | Assoc. Dr Chee Pun Ooi |
Date Deposited: | 30 Nov 2022 03:49 |
Last Modified: | 30 Nov 2022 03:49 |
URII: | http://shdl.mmu.edu.my/id/eprint/10652 |
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