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https://doi.org/10.70393/6a696...
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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The Application of Generative AI in Virtual Reality and Augmented Reality

Authors: Shijie Lyu;

The Application of Generative AI in Virtual Reality and Augmented Reality

Abstract

This study explores the historical development of Virtual Reality (VR) and Augmented Reality (AR) technologies and their applications in various fields, such as education, tourism, and consumer experiences. Through a review of relevant literature, the paper analyzes how VR and AR enhance user engagement and satisfaction by providing immersive and interactive experiences. In education, VR and AR are used to create vivid learning environments, promoting students' understanding and interest; in the tourism industry, these technologies enhance visitors' exploration and experience of destinations; in business, AR applications improve consumer shopping experiences and brand loyalty. Despite the widespread application of these technologies facing challenges such as high costs and user adaptability issues, research shows their potential remains significant. Future research should focus on optimizing user experience, lowering technological barriers, and expanding application scenarios. In conclusion, the development of VR and AR technologies will drive innovation and transformation across industries, offering richer experiences in daily life.

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    popularity
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    influence
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    impulse
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average