(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
During the last few decades, surveillance cameras have been installed in different locations just to watch manually. Object detection and analysis of the information captured using these cameras can play effective roles in event prediction, monitoring video feeds and goal-driven analysis applications including anomalies or intrusion detection. Large number of Artificial Intelligence techniques has been used to detect anomalies; amongst them Convolutional Neural Networks (CNN) using deep learning techniques improved the detection accuracy significantly. The goal of this article is to propose a new method based on deep learning techniques for Crime detection in video surveillance cameras. The proposed method has been evaluated in the UCSD dataset, and showed an increase in the accuracy of the Crime detection