Neural Network Design using a Virtual Reality Platform

Article ID

R0U06

AI-driven virtual reality for neural network design and deep learning applications. Enhances research with immersive tech.

Neural Network Design using a Virtual Reality Platform

Luigi Bibbò
Luigi Bibbò
Francesco Carlo Morabito
Francesco Carlo Morabito
DOI

Abstract

The evolution of Deep Learning (DL), a subset of machine learning, has made their use very effective in many artificial intelligence (AI) fields. In parallel Virtual Reality is going wide in many applications thanks to the proliferation of cameras in mobile devices and improved processing efficiency. Data visualization in deep learning is a fundamental element for which it can benefit from the advantages offered by the visualization of the VR for the development of the models. In addition, the researchers can widely use the editing of images and videos in the machine learning process to design a convolutional network suitable for image recognition. In this study, we want to demonstrate the usefulness of this approach in collecting data within virtual reality to train and optimize a convolutional neural network used to recognize human activities (HAR).

Neural Network Design using a Virtual Reality Platform

The evolution of Deep Learning (DL), a subset of machine learning, has made their use very effective in many artificial intelligence (AI) fields. In parallel Virtual Reality is going wide in many applications thanks to the proliferation of cameras in mobile devices and improved processing efficiency. Data visualization in deep learning is a fundamental element for which it can benefit from the advantages offered by the visualization of the VR for the development of the models. In addition, the researchers can widely use the editing of images and videos in the machine learning process to design a convolutional network suitable for image recognition. In this study, we want to demonstrate the usefulness of this approach in collecting data within virtual reality to train and optimize a convolutional neural network used to recognize human activities (HAR).

Luigi Bibbò
Luigi Bibbò
Francesco Carlo Morabito
Francesco Carlo Morabito

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Luigi Bibbò. 2026. “. Global Journal of Computer Science and Technology – D: Neural & AI GJCST-D Volume 22 (GJCST Volume 22 Issue D1): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Issue Cover
GJCST Volume 22 Issue D1
Pg. 45- 61
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GJCST-D Classification: F.1.1
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Neural Network Design using a Virtual Reality Platform

Luigi Bibbò
Luigi Bibbò
Francesco Carlo Morabito
Francesco Carlo Morabito

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