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在无人机图像中改善了麦田的杂草细分,并结合了消除模糊的细分模型

Nikita Genze1,2, Maximilian Wirth3,4, Christian Schreiner3

  • 1Technical University of Munich, TUM Campus Straubing for Biotechnology and Sustainability, Bioinformatics, Schulgasse 22, 94315, Straubing, Germany. nikita.genze@hswt.de.

Plant methods
|August 23, 2023
PubMed
概括

这项研究引入了DeBlurWeedSeg模型,该模型可以在无人机图像中准确地细分杂草,即使有动作模糊. 这有助于改善杂草管理和精准农业应用.

关键词:
计算机视觉 计算机视觉 计算机视觉揭开模糊的地方机器学习 机器学习分段化 分段化 分段化 分段化无人机无人机无人机是什么?杂草检测器可以检测杂草.

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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