Application of Neural Networks for Virtual and Augmented Reality

Abstract

The article analyzes modern virtual reality and augmented reality algorithms and ways of their implementation using neural networks. As a result, a classification of current virtual reality tasks is presented, the advantages and disadvantages of algorithms are identified, and the use of convolutional neural networks is proposed. As part of the study, a qualitative analysis of modern convolutional neural network architectures was carried out and their individual disadvantages when used in virtual reality systems were shown. As a result of the study, the optimal ways of applying neural networks in various tasks of identification, generativity and support in augmented and virtual reality systems were established. The functional and structural description of convolutional neural networks, the optimal structure and parameters for initialization and training of a convolutional neural network suitable for solving virtual reality problems are presented.