Hand Gestures Recognition and Tracking Within Virtual Reality using Hybrid Convolutional Neural Networks

Authors

DOI:

https://doi.org/10.18372/1990-5548.72.16940

Keywords:

convolutional neural network, virtual reality, machine learning, image classification, аdvanced RISC machine

Abstract

In this paper analysis of modern virtual reality algorithms based on mobile devices was done. As a result, algorithmic shortcomings were identified and the usage of convolutional neural networks was proposed. Within the research the qualitative analysis of modern architectures of convolutional neural networks was carried out and their separate shortcomings at use in systems on the basis of processor architecture аdvanced RISC machine was shown. As a result of this research it was found that to achieve the target accuracy and speed of the system it is important to use a hybrid convolutional neural network, which significantly improves the quality criteria of the system. The optimal structure and parameters for initialization and training of a hybrid convolutional neural network system used for virtual reality are obtained. The optimal training sample was formed and the use of pre-trained hybrid convolutional neural network on another device of аdvanced RISC machine architecture was described.

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

2022-09-23

Issue

Vol. 2 No. 72 (2022)

Section

AUTOMATION AND COMPUTER-INTEGRATED TECHNOLOGIES

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