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相关概念视频

Light Acquisition02:16

Light Acquisition

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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相关实验视频

Updated: Jun 26, 2026

Fruit Volatile Analysis Using an Electronic Nose
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Fruit Volatile Analysis Using an Electronic Nose

Published on: March 30, 2012

在水果园中检测杂草的数据集.

Andoni Salcedo-Navarro1, Guillem Montalban-Faet1, Miguel Garcia-Pineda1

  • 1Computer Science Department, ETSE-UV, Universitat de València, València, Spain.

Data in brief
|December 9, 2025
PubMed
概括

CampanetaWeed是一个新的多谱数据集,用于检测果园中的杂草. 该资源有助于开发用于可持续精准农业的先进机器学习模型.

科学领域:

  • 农业科学 农业科学
  • 计算机视觉 计算机视觉
  • 遥感 遥感 遥感 遥感

背景情况:

  • 永久作物中的杂草防治是昂贵的,并且对环境具有挑战性.
  • 有限的公共数据集阻碍了机器学习模型开发用于果园中杂草检测,特别是使用多光谱和多时间数据.
  • 现有的资源缺乏用于强大的跨频谱和季节性概括所需的全面数据.

研究的目的:

  • 介绍CampanetaWeed,一种用于果园环境中检测杂草的新型多谱图像数据集.
  • 为在精准农业中推进机器学习模型提供有价值的资源.
  • 促进对杂草识别的跨光谱适应和季节性概括的研究.

主要方法:

  • 使用DJI Mavic 3多光谱无人机在商业水果园上获取多光谱图像.
  • 数据集包括三次飞行 (2023年10月,2025年12月,2025年4月) 与像素对齐的RGB和四个窄带图像 (R,G,红边,NIR).
  • 用YOLOv5格式注释的图像,涵盖六种杂草物种和土壤干扰,总共超过10,000张图像和271,000个标记物体.

主要成果:

  • 在CampanetaWeed数据集提供高分辨率 (0.65厘米/像素GSD) 多光谱和多时间图像.
  • 综合性注释使杂草物种和土壤干扰的详细分析成为可能.
关键词:
阿拉乌吉亚 (Araujia sericifera) 是一种有序的植物.科尔塔德里亚·塞洛阿纳 (Cortaderia selloana) 是一家葡萄酒店.多光谱成像技术的使用.精准农业 精准农业 精准农业这种植物叫Rubus ulmifolius.无人机无人驾驶飞行器 (UAV) 是一个

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Last Updated: Jun 26, 2026

Fruit Volatile Analysis Using an Electronic Nose
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Published on: March 30, 2012

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Sieving Fruit Pulp to Detect Immature Tephritid Fruit Flies in the Field

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  • 该数据集旨在支持开发强大的杂草检测模型.

    • 结论:

    • CampanetaWeed提供了一个独特的,多谱的,多季节的数据集,对于在果园中推进杂草检测至关重要.
    • 该数据集将使得开发更准确,更强大的机器学习模型能够实现可持续的精准农业.
    • 该资源解决了专门数据集的稀缺性,促进了自动化杂草管理方面的创新.