Abstract

In the present paper we discuss a problem of recognition of a state of agricultural vegetation using aerial data of different spatial resolutions. To solve this problem, we develop a classifier allowing us to divide the input images into three classes, which are “healthy vegetation”, “diseased vegetation”, and “soil”. The proposed classifier is based on two convolutional neural networks allowing us to perform classification into two classes, namely “healthy vegetation” and “diseased vegetation” and “vegetation’ and “soil”.

中文翻译：

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基于卷积神经网络的航空数据农业植被监测

摘要

在本文中，我们讨论了使用不同空间分辨率的航空数据识别农业植被状态的问题。为了解决这个问题，我们开发了一种分类器，可以将输入图像分为“健康植被”，“病态植被”和“土壤”三类。所提出的分类器基于两个卷积神经网络，使我们能够将分类分为两类，即“健康植被”和“病态植被”以及“植被”和“土壤”。