机器学习驱动的增强现实技术在教育领域的应用调查综述

Haseeb Ali Khan, Sonain Jamil, Md. Jalil Piran, Oh-Jin Kwon, Jong-Weon Lee
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摘要

机器学习(ML)使增强现实(AR)在游戏、娱乐、医疗和教育等各个领域大受欢迎。ML 通过提供准确的物体可视化,增强了 AR 在教育领域的应用。对于 AR 系统,ML 算法有助于识别从幼儿园到大学的物体和手势。本调查旨在概述将 ML 技术应用于教育领域 AR 的各种方法。第一步是描述增强现实技术的背景。下一步,我们将讨论 AR 教育应用中使用的 ML 模型。此外,我们还将讨论如何在 AR 中使用 ML。通过分析这些框架,可以确定每个分组所面临的挑战和解决方案。此外,我们还概述了基于 ML 的 AR 教育框架的几个研究空白和未来研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comprehensive Survey on the Investigation of Machine-Learning-Powered Augmented Reality Applications in Education
Machine learning (ML) is enabling augmented reality (AR) to gain popularity in various fields, including gaming, entertainment, healthcare, and education. ML enhances AR applications in education by providing accurate visualizations of objects. For AR systems, ML algorithms facilitate the recognition of objects and gestures from kindergarten through university. The purpose of this survey is to provide an overview of various ways in which ML techniques can be applied within the field of AR within education. The first step is to describe the background of AR. In the next step, we discuss the ML models that are used in AR education applications. Additionally, we discuss how ML is used in AR. Each subgroup’s challenges and solutions can be identified by analyzing these frameworks. In addition, we outline several research gaps and future research directions in ML-based AR frameworks for education.
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