Jove
Visualize
联系我们

相关概念视频

Light Acquisition02:16

Light Acquisition

9.7K
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.
9.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Engineered zwitterion-nanodelivery for precision targeting of brain metastases.

Nature communications·2026
Same author

Expectation Violation Influences Neural Responses to the Accessibility of Cognitions Related to Suicide and Life: A Simultaneous EEG-fNIRS Study.

Brain sciences·2026
Same author

Linking changes in sulcal morphometry to cognitive development from childhood to adolescence.

Communications biology·2026
Same author

Spatiotemporal dynamics of the human cortical functional hierarchy across the lifespan.

Nature communications·2026
Same author

Automatic measurement of mesenteric vascular and portal vein parameters via PE-NET in the diagnosis of Crohn's disease.

Frontiers in medicine·2025
Same author

Expectation violation reduces the accessibility of implicit suicidal concepts and explicit life concepts.

Frontiers in psychology·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Feb 17, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

650

PointNeXt-DBSCAN:一个混合点云深度学习框架,用于多阶段棉花叶实例细分的混合点云.

Zeyu Lei1,2, Debin Zeng1,3, Liangfang Zheng1,3

  • 1College of Information Engineering, Tarim University, Alaer, China.

Frontiers in plant science
|February 16, 2026
PubMed
概括

这项研究引入了一个新的混合框架,用于从3D点云精确细分棉花叶. 该方法显著提高了识别单个叶子的准确性,有助于自动化植物表型.

关键词:
三维点云是3D点云.棉花植物的叶子 棉花植物的叶子深度学习是一种深度学习.多个阶段的增长监测.点云细分 分点云细分

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.6K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

835

相关实验视频

Last Updated: Feb 17, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

650
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.6K
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

835

科学领域:

  • 农业工程 农业工程
  • 计算机视觉 计算机视觉
  • 植物科学 植物科学

背景情况:

  • 棉花点云中的器官级实例细分由于形态变异和叶子封闭而具有挑战性.
  • 精确的叶子提取对于自动化表型和特征分析至关重要.

研究的目的:

  • 为棉花叶实例细分开发一个高精度的框架.
  • 为了应对细分棉花植物在不同生长阶段的挑战.

主要方法:

  • 提出了一个混合框架,将PointNeXt用于语义细分和密度适应的DBSCAN组合在一起,例如细分.
  • 构建和增强了1065家棉花厂的数据集.
  • 用于语义和实例细分的两个阶段管道被采用.

主要成果:

  • 语义细分实现了0.9846,比PointNet++有7.2%的改进.
  • 实例细分实现了0.983的调整后兰德指数 (ARI),减少了63%的过度细分.
  • 该框架保持了<3%的误差,叶子<5厘米2.

结论:

  • 拟议的混合框架为自动提取棉花关键表型特征提供了可靠的技术支持.
  • 这种方法提高了叶面积指数和叶面倾斜分布测量的准确性.
  • 该框架有效地处理棉花植物的形态变异和叶子封闭.