一种基于机器学习的电磁场分布测量方法

Ken Sato, Y. Kamimura
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引用次数: 0

摘要

本文介绍了用简易仪表显示电磁场分布的改进方法。可视化对于正确理解电磁场的生物效应具有重要意义。在这项研究中,使用一个简单的仪表代替传统的高性能仪表,可以更容易地测量。此外,本文还提出了一种方法,利用机器学习的目标检测技术,可以更容易地测量到测量位置,而以前的测量位置通常是红外标记或深度传感器。此外,通过使用机器学习纠正磁场传感器扫描角度造成的偏差,用户友好的测量是可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Simple Measurement Method of Electromagnetic Field Distribution using Machine-Learning
In this paper, the improvement of the visualization method of the electromagnetic field distribution using a simple meter is described. Visualization is important to correctly understand the biological effects from electromagnetic fields. In this study, it is possible to measure more easily by using a simple meter instead of the conventional high-performance meter. In addition, a method has been proposed in which the measurement position, which used to be an IR marker or depth sensor until now, can be measured more easily by using object detection by machine-learning. Furthermore, user-friendly measurement is possible by correcting the deviation due to the scanning angle of the magnetic field sensor using machine-learning.
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