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Semantic Segmentation to Identify and Treat Plants in a Field and Verify the Plant Treatments

机译:语义分割,以识别和处理野外植物并验证植物处理方法

摘要

A farming machine including a number of treatment mechanisms treats plants according to a treatment plan as the farming machine moves through the field. The control system of the farming machine executes a plant identification model configured to identify plants in the field for treatment. The control system generates a treatment map identifying which treatment mechanisms to actuate to treat the plants in the field. To generate a treatment map, the farming machine captures an image of plants, processes the image to identify plants, and generates a treatment map. The plant identification model can be a convolutional neural network having an input layer, an identification layer, and an output layer. The input layer has the dimensionality of the image, the identification layer has a greatly reduced dimensionality, and the output layer has the dimensionality of the treatment mechanisms.
机译:当农业机械在田间移动时,包括许多处理机构的农业机械根据处理计划对植物进行处理。农机的控制系统执行植物识别模型,该植物识别模型被配置为识别野外要处理的植物。控制系统生成处理图,该处理图标识要启动哪些处理机制来处理田间植物。为了生成处理图,农机捕获植物的图像,对该图像进行处理以识别植物,并生成处理图。植物识别模型可以是具有输入层,识别层和输出层的卷积神经网络。输入层具有图像的尺寸,识别层具有大大减小的尺寸,而输出层具有处理机构的尺寸。

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