SCALABLE OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE AND DEEP LEARNING
Keywords:
The use of artificial intelligence in surveillance systems, the detection of armed intruders, and the development of a faster RCNN (AI)Abstract
Due of the increased crime rate during
busy events or in suspiciously quiet regions, security
is always a major worry in every sector of life.
Computer vision has a wide range of applications in
the identification and monitoring of abnormalities.
Video surveillance systems that can detect and
analyse the scene and anomalous occurrences play an
important role in intelligence monitoring because of
the rising need for safety, security, and personal
property protection. The SS D and Faster RCNN
methods, which are based on convolution neural
networks (CNNs), are used in this study to create
automated gun (or weapon) identification. Two
datasets are used in the proposed implementation.
One dataset featured pre-labeled photographs, while
the other had images that had to be manually labelled
by the researcher. Algorithms may be used in realworld
scenarios depending on the tradeoff between
speed and accuracy, but results are summarized
