首页> 外文期刊>ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences >DETECTING iRUMEX OBTUSIFOLIUS/i WEED PLANTS IN GRASSLANDS FROM UAV RGB IMAGERY USING DEEP LEARNING
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DETECTING iRUMEX OBTUSIFOLIUS/i WEED PLANTS IN GRASSLANDS FROM UAV RGB IMAGERY USING DEEP LEARNING

机译:使用深度学习检测来自UAV RGB图像的草原中的 Rumex obtusifolius 杂草植物

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Broad-leaved dock (Rumex obtusifolius) is a fast growing and spreading weed and is one of the most common weeds in production grasslands in the Netherlands. The heavy occurrence, fast growth and negative environmental-agricultural impact makes Rumex a species important to control. Current control is done directly in the field by mechanical or chemical actuation methods as soon as the plants are found in situ by the farmer. In nature conservation areas control is much more difficult because spraying is not allowed. This reduces the amount of grass and its quality. Rumex could be rapidly detected using high-resolution RGB images obtained from a UAV and optimize the plant control practices in wide nature conservation areas. In this paper, a novel approach for Rumex detection from orthomosaics obtained using a commercial available quadrotor (DJI Phantom 3 PRO) is proposed. The results obtained shown that Rumex can be detected up to 90% from a 6 mm/pixel ortho-mosaic generated from an aerial survey and using deep learning.
机译:阔叶船坞(Rumex obtusifolius)是快速生长和蔓延的杂草,是荷兰生产草原中最常见的杂草之一。沉重的发生,快速增长和负面的环境 - 农业影响使Rumex成为对控制的重要性。一旦农民发现植物,就通过机械或化学致动方法直接在现场直接完成。在自然保护区内控制更加困难,因为不允许喷涂。这减少了草的数量及其质量。使用从无人机获得的高分辨率RGB图像可以快速检测RUMEX,并优化宽自然保护区中的工厂控制实践。本文提出了一种使用商业可用的四轮机器(DJI Phantom 3 Pro)获得的rumex检测的新方法。所得到的结果表明,RUMEX可以从航空测量和使用深度学习产生的6毫米/像素的邻摩卡酸中检测到90%。

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