使用机器学习模型检测和识别药丸

S. M, E. G, Amuthaguka. D, S. Akshaya, Anika C Uthaman, Snigdha Sridhar
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引用次数: 0

摘要

药丸颜色、药丸大小和形状是自动检测药丸的几个重要特征。但是,环境因素可能造成上述因素发生变化的影响。经常会发生用药错误,给患者造成并发症,这些都是由于标签损坏,药物摄入不匹配等原因造成的。本文提出了一种以Keras和Tensor Flow为核心的训练系统,用于快速、简便地识别药品品种。检测到的药丸(对象检测)连接到药丸数据库,其中检测到药丸名称。在检测过程之后,使用预训练的数据集来识别药丸。此外,数据集还将包括用例和所需的各自药丸的详细信息。该项目包括为自动药物检测技术收集数据集。实验结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection and Identification of Pills using Machine Learning Models
Pill color, pill size and shape are few important characteristics for automatic pill detection. However, the environmental factors may cause an effect such that a change is produced in the above factors. Often medication errors occur that may cause complications to patients and all these are caused due to damage in labels and mismatches in medicine intake, etc. In this report, a trained system is proposed using Keras and Tensor Flow mainly, for easy and quick identification of varieties of pills. The detected pill (object detection) connects to the pill database wherein the pill name is detected. After the process of detection, the pre-trained dataset is used to identify the pill. Moreover, the dataset would also include the use cases and required detailed information of the respective pill. The project involves collecting datasets for automated medicine detecting technology. Effectiveness of the proposed method can be verified in the experimental results.
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