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 (Unpublished)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
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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