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Ecological evolution path of smart education platform based on deep learning and image detection

机译：基于深度学习和图像检测的智能教育平台生态演变路径

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摘要

Smart environments are becoming a reality in our society, and the number of smart devices integrated into these spaces is overgrowing. End users are being provided a simplified way to handle complex smart features, as the combination of smart elements opens up a wide range of new opportunities to facilitate. This article explores the significant challenges to be overcome in designing an intelligent educational environment for the main characteristics and the personalized support of ecology. To integrate intelligent learning environments into learning ecology and educational environments, innovative applications, and new teaching methods should be implemented to coordinate formal and informal learning. However, despite the increased use of smart learning environments in higher education, at the same time, there is an excellent network that does not define a set of demand models for the development and evaluation of smart learning environment education that considers teaching, evaluation, and design. Deep learning is one of the modern methods that can be used to automate the process of effective intellectual education based on image detection. The deep learning process is based on image discovery. It provides an overview of ecological evaluation based smart education level analysis used image detection. The system that has been proposed here is an intelligent education system that has been customized to provide the resources of the evolution of the ecosystem to the learner to suit their perceptions and education center to start the platform.
机译：智能环境正在成为我们社会的现实，集成到这些空间中的智能设备的数量过度划分。最终用户正在提供一种简化的方法来处理复杂的智能功能，因为智能元素的组合开辟了各种新的机会，以方便。本文探讨了设计智能教育环境的重大挑战，以实现主要特点和生态的个性化支持。将智能学习环境集成到学习生态和教育环境，创新应用程序和新的教学方法中，并应实施新的教学方法，以协调正式和非正式学习。但是，尽管在高等教育中使用了智能学习环境的增加，但同时，有一个很好的网络，没有为智能学习环境教育的开发和评估来定义一系列需求模型，以考虑教学，评估和设计。深度学习是可用于自动化图像检测的有效智力教育的过程之一的现代方法之一。深度学习过程基于图像发现。它概述了基于生态评估的智能教育水平分析使用的图像检测。这里提出的系统是一个智能教育系统，已被定制，以便为学习者提供生态系统的演变的资源，以适应他们的看法和教育中心开始平台。

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