Intelligent Video Moving Target Detection Based on Multi-Attribute Single Value Medium Neutrosophic Method

Abstract

Competition in social sports has many benefits for athlete training due to this competition gives researchers a chance to making and developing new methods and ways that support them. The competition in sport growth rapidly these days. During the last several years, there has been a significant increase in the volume of traffic using multimedia. In addition, some of the most recent paradigm shifts suggested, such as IoT, bring about the introduction of new kinds of traffic and applications. Software-defined networks, often known as SDNs, are beneficial to network management since they enhance its capabilities. When used with SDN, artificial intelligence (AI) has the potential to solve network issues using categorization and estimate strategies. So, in this paper discuss and develop a new method for sports video moving target detection. This method is based on multi-criteria decision making (MCDM) because targeting detection has many criteria and sub-criteria. This paper collected five main criteria and twenty sub-criteria impacts in target detection of sports video. We use the Analytical hierarchy Process (AHP) to determine the importance of these criteria and their weights. These criteria were evaluated under a neutrosophic environment. An application is provided to measure the outcome of the proposed method.