基于机器学习算法的计算机视觉训练工具包设计,以克服COVID-19大流行期间的远程学习

D. Kuswardhana, E. Haritman, F. Jabbar, F. Nashrullah
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摘要

COVID-19大流行期间的情况迫使教育系统采取了不同的学习方式。本文介绍了如何通过计算机视觉培训工具包进行实验室训练,以克服大流行期间的远程学习。因此,学生(作为用户)可以在任何地方使用它。使用的环境是在NVIDIA Jetson Nano单板计算机上。方法是使用瀑布模型。访问培训包的方法是使用通过流媒体网站连接到设备上的用户摄像头上的摄像头输入。我们使用远程桌面协议建立连接,工具的IoT部分使用Antares Cloud Storage。因此,可以通过计算机视觉程序来改变ESP32微控制器中的器件状态。因此,整个过程可以在另一个包含每个模块的过程摘要的门户网站上进行检查。©2023作者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of computer vision training kit with machine learning algorithm to overcome distance learning in pandemic COVID-19
The situation in the pandemic COVID-19 period has forced the education system to come into a different way of learning. This paper has oriented how to present laboratory workouts through a computer vision training kit to overcome distance learning in the pandemic. Thus, students (as the user) can use it anywhere. The environment used is on a Single Board Computer of NVIDIA Jetson Nano. The method is using the waterfall model. The way to access the training kit is to use the camera input on the user camera attached to their device connected through a streaming website. We establish the connection using the Remote Desktop Protocol, and The IoT part of the tool uses Antares Cloud Storage. Thus, the device state in the ESP32 microcontroller could be changed by the computer vision program. The entire process, as a result, can be inspected on another web portal containing the summary of the process on each module. © 2023 Author(s).
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