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METHOD FOR CONSTRUCTING FARMLAND IMAGE-BASED CONVOLUTIONAL NEURAL NETWORK MODEL, AND SYSTEM THEREOF

机译:基于农田图像的卷积神经网络模型构建方法及其系统

摘要

A method for constructing a convolutional neural network model based on farmland images is illustrated. The method includes following steps: obtaining a number of farmland images of at least one farmland; obtaining a plurality of standard segmentation farmland images corresponding to each of the farmland images; dividing the farmland images and the standard segmentation farmland images into a training image set and a test image set; taking the farmland images and the standard segmentation farmland images in the training image set as input of a convolutional neural network, and constructing a convolutional neural network model based on the farmland images; and verifying the convolutional neural network model by using the farmland images in the test image set and the standard segmentation farmland images, and optimizing a plurality of parameters of the convolutional neural network model based on the farmland images.
机译:提出了一种基于农田图像的卷积神经网络模型的构造方法。该方法包括以下步骤:获取至少一个农田的多幅农田图像;获取与每个农田图像对应的多个标准分割农田图像;将农田图像和标准分割农田图像划分为训练图像集和测试图像集;将训练图像集中的农田图像和标准分割农田图像作为卷积神经网络的输入,基于农田图像构建卷积神经网络模型;以及使用测试图像集中的农田图像和标准分割农田图像验证卷积神经网络模型,并基于农田图像优化卷积神经网络模型的多个参数。

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