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Cashew Trees Detection And Yield Analysis Using UAV-Based Map

机译:基于UV的地图的腰果树检测和产量分析

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In this study we developed a novel method to detect cashew trees in an orthophoto map derived from images collected by an unmanned aerial vehicle (UAV). We also suggest a way in which these detections can be used to analyze the yield of the cashew farm. The proposed method uses image analysis to find the tops of trees, to merge different tops located on the same tree, and to segment individual tree. The segmented trees are used in a deep learning framework to know the exact location of cashew trees. The preliminary cashew detection from UAV-based map is promising. This study can be interesting for developing countries where UAV system are nowadays gaining popularity in agriculture. Our method does not require any additional sensor other than the RGB camera onboard the UAV. This low-cost solution is suitable for small and medium cashew farmers. The developed method can also be extended to other types of trees, other than the cashew.
机译:在这项研究中,我们开发了一种新的方法,用于检测来自由无人机(UAV)收集的图像的正芯片地图中的腰果树木。 我们还建议使用这些检测来分析腰果农场的产量。 该方法使用图像分析来查找树的顶部,以合并位于同一树上的不同顶部,并分段为单个树。 分段树用于深入学习框架,以了解腰果树的确切位置。 基于UV的地图的初步腰果检测是有前途的。 这项研究对于发展中国家现在对自然的发展中国家来说,这项研究可能很有趣。 我们的方法不需要除了UAV时除了RGB相机之外的任何附加传感器。 这种低成本的解决方案适用于中小型腰果农民。 除了腰果之外,开发的方法也可以扩展到其他类型的树木。

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