Application of Neural Networks for Virtual and Augmented Reality

Authors

DOI:

https://doi.org/10.18372/1990-5548.74.17296

Keywords:

neural networks, virtual reality, machine learning, image identification, 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.

Author Biographies

Victor Sineglazov , National Aviation University, Kyiv

Doctor of Engineering Science

Professor. Head of the Department

Aviation Computer-Integrated Complexes Department

Faculty of Air Navigation, Electronics and Telecommunications

Illia Boryndo , National Aviation University, Kyiv

Post-graduate student

Faculty of Air Navigation, Electronics and Telecommunications

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Published

2022-12-29

How to Cite

Sineglazov , V., & Boryndo , I. (2022). Application of Neural Networks for Virtual and Augmented Reality. Electronics and Control Systems, 4(74), 51–57. https://doi.org/10.18372/1990-5548.74.17296

Issue

Vol. 4 No. 74 (2022)

Section

AUTOMATION AND COMPUTER-INTEGRATED TECHNOLOGIES

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