Training video surveillance system for the purpose of object identification with the help of neural networks

Abstract

Research on the development of algorithms for the use of neural networks associated with video surveillance systems on the identification of the desired objects today go to a whole new technological level. Categorization of classes-objects of research, determination of actual zones of fixation, integration of functions-cloud computing, analysis of incoming data and their evaluation determine the relevance in the creation of a trainable model that allows to solve a wide range of problems when working with the existing and the flow of incoming data in real time both at the state and at the level of transnational companies.