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Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era

In recent years, with the rapid development of emerging Internet of Things technology and short-range wireless communication technology, smart healthcare monitoring network technology has become a research hotspot. It provides convenience for people and enhances the development of people's own...

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Detalles Bibliográficos
Autor principal: Feng, Jianwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273351/
https://www.ncbi.nlm.nih.gov/pubmed/35832246
http://dx.doi.org/10.1155/2022/3965416
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author Feng, Jianwen
author_facet Feng, Jianwen
author_sort Feng, Jianwen
collection PubMed
description In recent years, with the rapid development of emerging Internet of Things technology and short-range wireless communication technology, smart healthcare monitoring network technology has become a research hotspot. It provides convenience for people and enhances the development of people's own healthcare awareness. This paper aims to study how to make its application in the field of smart healthcare education more applicable through the use of related technologies in the Internet of Things era and few-shot learning. For this reason, this paper proposes to optimize and improve the new sensor technology and the algorithm of few-shot learning, and to adjust some parameters as a whole. At the same time, related experiments and analysis are designed for the improved algorithm to study and understand its performance. The experimental results in this paper show that the improved algorithm improves its application effect by 36.9% and is relatively more applicable than the unimproved algorithm.
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spelling pubmed-92733512022-07-12 Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era Feng, Jianwen Comput Intell Neurosci Research Article In recent years, with the rapid development of emerging Internet of Things technology and short-range wireless communication technology, smart healthcare monitoring network technology has become a research hotspot. It provides convenience for people and enhances the development of people's own healthcare awareness. This paper aims to study how to make its application in the field of smart healthcare education more applicable through the use of related technologies in the Internet of Things era and few-shot learning. For this reason, this paper proposes to optimize and improve the new sensor technology and the algorithm of few-shot learning, and to adjust some parameters as a whole. At the same time, related experiments and analysis are designed for the improved algorithm to study and understand its performance. The experimental results in this paper show that the improved algorithm improves its application effect by 36.9% and is relatively more applicable than the unimproved algorithm. Hindawi 2022-07-04 /pmc/articles/PMC9273351/ /pubmed/35832246 http://dx.doi.org/10.1155/2022/3965416 Text en Copyright © 2022 Jianwen Feng. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Feng, Jianwen
Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era
title Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era
title_full Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era
title_fullStr Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era
title_full_unstemmed Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era
title_short Application of New Sensor Technology and Few-Shot Learning in Education Based on IoT Era
title_sort application of new sensor technology and few-shot learning in education based on iot era
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273351/
https://www.ncbi.nlm.nih.gov/pubmed/35832246
http://dx.doi.org/10.1155/2022/3965416
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