Abstract
Automatic video surveillance can assist security personnel in the identification of threats. Generally, security personnel are monitoring multiple monitors and a system that would send an alert or warning could give the personnel extra time to scrutinize if a person is carrying a firearm. In this paper, we utilize Google’s Tensorflow API to create a digital framework that will identify handguns in real time video. By utilizing the MobileNetV1 Neural Network algorithm, our system is trained to identify handguns in various orientations, shapes, and sizes, then the intelligent gun identification system will automatically interpret if the subject is carrying a gun or other objects. Our experiments show the efficiency of implemented intelligent gun identification system.
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Singleton, M., Taylor, B., Taylor, J., Liu, Q. (2018). Gun Identification Using Tensorflow. In: Meng, L., Zhang, Y. (eds) Machine Learning and Intelligent Communications. MLICOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-00557-3_1
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DOI: https://doi.org/10.1007/978-3-030-00557-3_1
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