Integrating Artificial Intelligence and Deep Learning for the Purpose of Detecting Arms in Defense
S. Sandhya · International Journal for Research in Applied Science and Engineering Technology · 2023
Abstract: There has been an increase in the relevance of security as a primary issue across all sectors as a result of the prominence of criminal activities that take place at public events or in settings that seem to be distant. It is important to note that computer vision plays a vital role in the fields of anomaly detection and monitoring. It provides a broad range of applications that may be used to handle a variety of issues. The technology of computer vision is used in several applications. An essential component of the intelligence monitoring process is the use of video surveillance systems that are equipped with the capacity to identify and assess the surrounding environment, in addition to identifying and analysing unexpected events. The explanation for this occurrence is that there is a rising need to protect personal assets, and there is also an increased focus on ensuring that there is an increased degree of safety and security. This study makes use of a Yolo algorithm in order to effectively accomplish the goal of automating the identification of guns and other types of weapons. The method that is being presented involves the use of two distinct types of datasets. The first dataset is made up of images that have already been classified, whereas the second dataset is made up of photographs that have been manually labelled. The use of these datasets is available to the public. Despite the fact that the laborious tabulation of data is carried out with accuracy, the actual use of these findings in real-world circumstances may be contingent on the delicate balance that is established between speed and precision.