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Water Meter Reading Area Detection Based on Convolutional Neural Network

机译:基于卷积神经网络的水表读取区域检测

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The water meter is a device for measuring the amount of water used by each household. Remote meter reading is one of the main ways to solve the waste of human resources caused by regular manual door-to-door access to mechanical water meter readings. The current use of image acquisition and then accurate reading of the water meter image is one of the ways of remote meter reading. In this paper, the convolutional neural network is used to predict the reading area, and then the non-maximum suppression algorithm (NMS) is used to remove highly overlapping results from prediction region results to obtain the position of the reading area. The experimental results show that with using the method proposed in this paper in the actual application scenario, the IoU of the images of 1000 test sets are all above 0.8 and then combined with the three-layer BP neural network for character recognition, the accuracy rate reaches 98.0%.
机译:水表是用于测量每个家庭使用的水量的装置。远程抄表是解决由常规手动门到门接入机械水表读数造成的人力资源浪费的主要方法之一。目前使用图像采集,然后准确地读取水表图像是远程抄表读数之一。在本文中,卷积神经网络用于预测读取区域,然后使用非最大抑制算法(NMS)来从预测区域结果中去除高度重叠的结果,以获得读取区域的位置。实验结果表明,在实际应用场景中使用本文提出的方法,1000个测试集的图像的IOO在0.8以上,然后与三层BP神经网络组合进行性格识别,精度率达到98.0%。

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