Medicine Classification Using YOLOv4 and Tesseract OCR

C. Paglinawan, Marielle Hannah Caliolio, Joshua Frias
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引用次数: 1

Abstract

For seniors, consuming the incorrect pharmaceutical drug is a common but serious medical issue. Poor vision, difficulty reading, impaired memory, and problems with fine-motor skills are all factors that might lead to using the incorrect pharmaceutical drug. Previous studies have created systems that can automatically identify medications to address this issue. Although, this research lacked the integration of the latest official version of YOLO and the Tesseract OCR. As such, the researchers developed a system that can classify medicines using YOLOv4 and Tesseract OCR. Through tests, YOLOv4 was established to be the best in accuracy (~95% accuracy), followed by YOLOv4 and Tesseract OCR together (~19% accuracy). The least accurate one was using the Tesseract OCR only (~14% accuracy).
使用YOLOv4和Tesseract OCR进行药物分类
对于老年人来说,服用不正确的药物是一个常见但严重的医疗问题。视力不佳、阅读困难、记忆力受损以及精细运动技能问题都可能导致使用不正确的药物。以前的研究已经创建了可以自动识别药物的系统来解决这个问题。虽然本研究缺乏最新官方版本的YOLO和Tesseract OCR的整合。因此,研究人员开发了一种可以使用YOLOv4和Tesseract OCR对药物进行分类的系统。通过测试,确定YOLOv4的准确率最高(~95%),其次是YOLOv4和Tesseract OCR一起使用(~19%)。准确度最低的是只使用Tesseract OCR(~14%的准确度)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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