ARChem: Augmented Reality Chemistry Lab

Menikrama, M.R.L.Y; Liyanagunawardhana, C.S; Amarasekara, H.G.D.M.I; Ramasinghe, M.S; Weerasinghe, Lokesha; Weerasinghe, I.

doi:10.1109/iemcon53756.2021.9623121

Cited by 2 publications

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It excels in chemical equation identification and correction, image processing, text summarization, and even sentiment analysis through a Chatbot. The fusion of mobile development techniques, ML, and DL makes ARChem a game-changer in the realm of virtual education, aiming to alleviate the challenges students face in comprehending and applying complex chemistry concepts [84].…”

Section: Archem For Chemistry Educationmentioning

confidence: 99%

A Comprehensive Survey on the Investigation of Machine-Learning-Powered Augmented Reality Applications in Education

Khan,

Jamil,

Piran

et al. 2024

Technologies

View full text Add to dashboard Cite

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.

show abstract

Section: Archem For Chemistry Educationmentioning

confidence: 99%

A Comprehensive Survey on the Investigation of Machine-Learning-Powered Augmented Reality Applications in Education

Khan,

Jamil,

Piran

et al. 2024

Technologies

View full text Add to dashboard Cite

show abstract

Section: Archem For Chemistry Educationmentioning

confidence: 99%

A Comprehensive Survey on Investigation of Machine Learning-Powered Augmented Reality Applications in Education

Khan,

Jamil,

Jalil Piran

et al. 2024

Preprint

View full text Add to dashboard Cite

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 will 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.

show abstract

ARChem: Augmented Reality Chemistry Lab

Cited by 2 publications

References 2 publications

A Comprehensive Survey on the Investigation of Machine-Learning-Powered Augmented Reality Applications in Education

A Comprehensive Survey on the Investigation of Machine-Learning-Powered Augmented Reality Applications in Education

A Comprehensive Survey on Investigation of Machine Learning-Powered Augmented Reality Applications in Education

Contact Info

Product

Resources

About