自动化仪表测量中的智能识别

A. Ivashchenko, A. Krivosheev, Denis Sveshnikov, Nikita Svechkov, Tatiana Feschenko, Yuliya Tyshkovskaya, A. Chuvakov
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引用次数: 0

摘要

本文提出了一种新的多层解决方案,将实现人工智能(AI)的各种算法结合起来用于图像识别。引入了几种神经网络来解决具体的目标识别问题。补充了额外的“预发布匹配器”,以确定各种对象并将其分配给最相应的AI模块。以分布式仪表测量为例,说明了其成功的应用。所介绍的解决方案用于处理和分析电表的结果,这些结果由一组巡逻人员检查人员使用手持设备进行手动监控。开发和测试的结果表明,在实际应用中,神经网络用于仪表处理的质量是可以提高的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Recognition in Automated Meters Surveying
The paper proposes a new multi-layer solution to combine various algorithms implementing Artificial Intelligence (AI) for image recognition. Several neural networks are introduced to solve specific problems of objects identification. Additional “pre-launch matcher” is supplemented to scope out various objects and assigns them to the most corresponding AI modules. Distributed meter surveying is taken as an illustrative example of successful use. The introduced solution was implemented to process and analyze the results of electrical meters that are manually monitored by a group of patrol personnel inspectors using hand held devices. The results of development and testing show how the quality of neural network used for meter processing can be improved in practice.
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