医药包装识别遗传方法的发展

I. Fedorchenko, A. Oliinyk, D. Goncharenko, Alexander Stepanenko, Tetiana Fedoronchak, Anastasia Kharchenko, Peter Langendörder
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引用次数: 1

摘要

研究了药品包装到货时的自动定义问题。分析了信息系统中模式识别的主要方法。讨论了识别领域存在的问题及其解决方法。为了使分拣只到药房的药品的过程自动化,对预先准备好的分拣机器人的神经网络进行了修改,在此神经网络的基础上,分拣机器人将在包装分析后给出确切的名称,这将减少填写发票的时间。进行了图像增强,从而改善了结果。介绍了一种用于寻找和优化神经网络结构的遗传算法。结果表明,该方法提高了识别精度。此解决方案将简化第一张表的工作,并更多地关注客户以避免排队。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a Genetic Method for the Recognition of Medical Packaging
The problem of automation of definition of medical packages on arrival at a drugstore is considered. The main methods of pattern recognition in information systems are analyzed. Problems in the field of recognition and methods of their solution are considered. To automate the process of sorting only incoming drugs to the pharmacy department, a modification of the pre-prepared neural network for the robot sorter was developed, which on the basis of this neural network will give the exact name after packaging analysis, which will reduce the time to fill out the invoice. Image augmentation was performed, which allowed to improve the result. The introduction of a genetic algorithm for finding and optimizing the neural network architecture was also carried out. As a result, an increase in recognition accuracy was obtained. This solution will simplify the work for the first table and pay more attention to customers to avoid queues.
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