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PharmaCV: A Cloud Vision Approach on Generating Labels of Pharmaceutical Drugs

机译:Pharmacv:发电药物标签的云视觉方法

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This paper presents a novel and straightforward way of generating labels from images of common pharmaceutical drugs found in the Philippine market using Cloud Vision. The images used were given labels that indicate the name of the drug and its language code used, the application of the drug, other alternate names of the drug and related labels with their corresponding confidence scores. In addition to that, the uniform resource locator or URL that direct to pages with full and partial matching images were given. Furthermore, the images were stored in a cloud storage bucket which offers good documentation, a high durability of 99.99%, in which the data survives even in the event of simultaneous losses, and easy integration with state-of-the-art Google cloud services such as AutoML, Kubernetes, Compute Engine. The Cloud Vision API was used due to its superb features compared to the similar computer vision APIs that are existing today. This study will be useful to both medical practitioners and drug users since it will be easier for them to gather all the necessary information about a particular drug from its image alone. Furthermore, the system developed in this study can be used in drug dispensing machines where the drug users can be provided enough information about the drug and its applications despite having little knowledge about them.
机译:本文介绍了利用云视觉在菲律宾市场发现的普通药物的图像中产生标签的新颖和直接的方式。使用的图像是给出的标签,指示药物的名称及其语言代码,药物的应用,药物的其他替代名称和相关标签的应用相应的置信分数。除此之外,还给出了直接与完整和部分匹配图像的页面的统一资源定位器或URL。此外,图像存储在云存储桶中,提供良好的文档,高耐久性为99.99%,其中数据甚至在同时损失的情况下存活,并且与最先进的谷歌云服务轻松集成如Automl,Kubernetes,Compute Engine。与其今天存在的类似计算机视觉API相比,由于其优化特性使用了云视觉API。这项研究对于医生和吸毒者来说都是有用的,因为他们将更容易地收集有关特定药物的所有必要信息。此外,本研究开发的系统可用于药物分类机中,尽管对它们有很少了解,但可以提供有关药物及其应用的足够信息。

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