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Updated: May 15, 2025

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使用神经辐射场和轻量级点云细分网络进行植物茎和叶片细分和表型参数提取

Gaofei Qiao1, Zhibin Zhang1, Bin Niu1

  • 1Key Laboratory of Wireless Networks and Mobile Computing, School of Computer Science, Inner Mongolia University, Hohhot, China.

Frontiers in plant science
|April 11, 2025
PubMed
概括

本研究提出了一种新的3D植物重建和细分方法,用于准确的表型特征提取. 开发的PointSegNet实现了对玉米,西红和大豆植物进行细分的高准确性,用于智能农业应用.

关键词:
轻量级网络轻量级的网络.神经辐射场是一个神经辐射场.植物现象型 植物现象型点云细分 分点云细分三维点云是一个三维点云.

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Light Acquisition02:16

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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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