基于安卓系统的极端学习机检测(Miopi)实施方案

Thias Rizqi Wijaya, R. Rachman
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引用次数: 0

摘要

近视是相当影响日常生活的眼部疾病之一,因为如果不治疗,病情会不断变化,其中一个辅助工具就是眼镜。由于近视度数不断增加,眼镜的使用很快就会发生变化,而大多数患者又不愿意重新检查近视度数,这就增加了时间或成本。本研究旨在找到应用极端学习机检测近视的最佳准确值,并帮助检测患者的负视眼数量。研究中使用的方法是极限学习机(ELM)方法。之所以选择这种方法,是因为它能很好地处理图像形式的数据,并产生良好的准确性。本研究的结果包括准确度、精确度和再现性,以及以移动应用程序形式输出的应用结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMPLEMENTASI EXTREME LEARNING MACHINE UNTUK DETEKSI RABUN JAUH (MIOPI) BERBASIS ANDROID
Nearsightedness is one of the eye disorders that quite interfere with daily life because the condition continues to change if not treated, one auxiliary tool is glasses. The use of glasses is not uncommon to quickly change because of the increasing minus and most sufferers are reluctant to re-examine the minus condition which increases due to time or cost. This study aims to find the best accuracy value from the application of extreme learning machines for nearsightedness detection and to help detect the amount of minus eye in patients. The method used in research is the Extreme learning machine (ELM) method. The choice of this method is due to how it works wel for processing data in the form of images and produces good accuracy. The results of this study are the magnitude of accuracy, precision ,and recal as wel as the output of the application in the form mobile application.
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