izvorni znanstveni rad
Ensuring safety and trust in city and state institutions are key elements of human rights. Citizens of urban areas strive for safe passage through the main squares and streets in order to return to their homes carefree. Unfortunately, technological developments and sometimes distorted worldviews lead to a worsening of the situation, including an increase in armed attacks, violent crimes and terrorist threats. This research focuses on the application of artificial intelligence, specifically convolutional neural networks, to improve computer vision models. By using the latest YOLOv9 algorithm, high performance is achieved in the detection, classification and localization of the displayed elements, with promising results of mean average precision (mAP) of 0.92, and Precision, Recall and F1-score which are 0.98, 0.99 and 0.98 respectively. The data used in the research, obtained from a public repository, includes different recording conditions, including night conditions, which further emphasizes the relevance of this research.
object detection, urban security, weapon detection, YOLOv9
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