基于深度学习技术的云电子学习平台改进计算解决方案

Wenyi Xu
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引用次数: 1

摘要

共享的电子学习平台可以在云计算基础设施上为学生提供一个有用的学习环境。虚拟教室正在暂时取代传统教室,这意味着电子学习正变得越来越流行。目前还没有估算将使用多少云资源的策略。因此,学生可以访问学习对象,而无需决定遵循不同的学习管理系统(LMS)。所提出的基于深度学习的电子学习平台(DL-E-LP)可以使嵌入在多个电子学习标准中的独立LMS共享学习对象。使用智能学习系统,教师可以更容易地跟踪学生的进步。卷积神经网络已被用于人脸识别和深度学习中学生知识学习水平的监测。现代科技和智能教室的使用使所有学生的学习更容易。通过实验,提出的范例既有效又富有成效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Computational Solution for Cloud-Enabled E-Learning Platforms Using a Deep Learning Technique
The sharable e-learning platform can be presented as a useful learning environment for students on the cloud computing infrastructure. Virtual classrooms are momentarily taking the place of conventional ones, which means that e-learning is becoming more popular. There are currently no strategies for estimating how much cloud resources will be used. Because of this, students can access learning objects without deciding to follow a different learning management system (LMS). The proposed deep learning-based e-learning platform (DL-E-LP) can enable separate LMS embedded in multiple e-learning standards to share the learning objects. Using a smart learning system, teachers can keep track of their students' progress more easily. The convolutional neural network has been used to develop face recognition and monitor students' knowledge learning level in deep learning. The use of modern technologies and smart classrooms makes learning easier for all students. The proposed paradigm is both efficient and productive through experimentation.
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