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Grain quality control system and method

机译:粮食质量控制系统与方法

摘要

A method and system for controlling the quality of harvested grains include capturing, by one or more image sensors, one or more images of material at a sampling location within a grain elevator of the combine harvester. The captured images are defined by a set of image pixels represented by image data and having a classification feature indicative of grain or non-grain material. One or more controllers receive the image data associated with the one or more images captured by the image sensor(s) and select a sample image defined by a subset of image pixels of the set of image pixels. The controller(s) apply a convolutional neural network (CNN) algorithm to the image data of the subset of image pixels of the selected sample image to determine the classification feature. The controller(s) analyze the determined classification feature to adjust an operational parameter of the combine harvester.
机译:用于控制收获晶粒质量的方法和系统包括通过一个或多个图像传感器捕获,在组合收割机的谷物电梯内的采样位置处的一个或多个材料图像。 捕获的图像由由图像数据表示的一组图像像素限定,并且具有指示谷物或非粒材料的分类特征。 一个或多个控制器接收与由图像传感器捕获的一个或多个图像相关联的图像数据,并选择由该组图像像素的图像像素的子集定义的样本图像。 控制器(S)将卷积神经网络(CNN)算法应用于所选择的样本图像的图像像素子集的图像数据以确定分类特征。 控制器分析所确定的分类功能以调整组合收割机的操作参数。

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