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The Optimization of Digital Art Teaching Platform Based on Information Technology and Deep Learning

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成果类型:
期刊论文
作者:
Liu, Yiying;Ko, Young Chun
通讯作者:
Ko, YC
作者机构:
[Liu, Yiying] Hunan City Univ, Coll Fine Arts & Design, Yiyang 413000, Hunan, Peoples R China.
[Liu, Yiying] Sehan Univ, Grad Sch, Dept Educ, Chungnam 58447, South Korea.
[Ko, Young Chun; Ko, YC] Sehan Univ, Dept Teaching Profess, Chungnam 58447, South Korea.
通讯机构:
[Ko, YC ] S
Sehan Univ, Dept Teaching Profess, Chungnam 58447, South Korea.
语种:
英文
关键词:
Education;Digital art;Internet of Things;Sensors;Real-time systems;Optimization;Surveys;Information technology;Deep learning;deep learning;digitization;teaching platform
期刊:
IEEE ACCESS
ISSN:
2169-3536
年:
2023
卷:
11
页码:
107287-107296
基金类别:
Research Funds from Sehan University, South Korea, in 2023
机构署名:
本校为第一机构
摘要:
The study aims to improve the daily teaching level of the school and make students enjoy better teaching methods. Firstly, the Internet of Things (IoT) and deep learning (DL) are deeply studied through information technology (IT). Secondly, the calculation methods based on the IoT and DL are analyzed, through which the research model is constructed. Finally, a digital teaching platform is established through the research model to conduct a real-time statistical survey of students and teachers. The results show that students are leading in the d...

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