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PART REPLACEMENT PREDICTIONS USING CONVOLUTIONAL NEURAL NETWORKS

机译:使用卷积神经网络的零件替换预测

摘要

An example of an apparatus including a communication interface to receive an image file is provided. The image file represents a scanned image of a output generated by a printing device. The apparatus further includes an identification engine to process the image file with a convolutional neural network model to identify a feature. The feature may be indicative of a potential failure. The apparatus also includes an image analysis engine to indicate a life expectancy of a part associated with the potential failure based on the feature. The image analysis engine uses the convolutional neural network model to determine life expectancy.
机译:提供了包括通信接口以接收图像文件的设备的示例。图像文件表示由打印设备生成的输出的扫描图像。该设备还包括识别引擎,以利用卷积神经网络模型处理图像文件以识别特征。该特征可以指示潜在的故障。该设备还包括图像分析引擎,以基于该特征来指示与潜在故障相关联的部件的预期寿命。图像分析引擎使用卷积神经网络模型来确定预期寿命。

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