Methods and technologies of machine learning in neural network for computer vision purposes

Abstract

This article is devoted to an overview of the current state and development prospects in the field of machine learning technologies application in computer vision problems. The article discusses the types of architectures of deep convolutional networks used for image processing, discusses their application in the space industry and provides an analysis of the element base for the implementation of computer vision platforms. The aim was to research the machine learning methods in computer vision problems. Consideration of options for using neural networks in solving problems related to astronautics. The authors considered various methods and technologies of machine learning using both domestic and foreign devices. The study showed that at the moment there are several domestic companies that are engaged in the development of microprocessors, on which it is possible to implement a neural network and train it. Also, the prospects of machine learning in computer vision problems, their possibility and feasibility of application at the present time and in the near future were identified. The results of the work can be used to create various types of neural networks. Based on the above overview of neural processors, you can begin to design a neural network. The processing and dumping of incoming information, necessary for machine learning, is able to control functions, solve emergency situations and protect human life.