相关实验视频

Updated: Jul 11, 2025

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

Published on: August 8, 2017

植物根从RGB (迷你) 根子图像的语义细分 - - 既定方法和先进的深度学习模型的概括潜力和错误阳性

Pavel Baykalov^1,2, Bart Bussmann³, Richard Nair^4,5

¹Institute of Forest Ecology, Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU), Vienna, Austria.

|November 6, 2023

概括

深度学习模型,特别是U-Net架构,显著改善了微型图像中的语义根细分. 这些模型在各种数据集中提高了准确性和通用性,减少了手动分析时间.

科学领域:

植物科学植物科学
计算机视觉计算机视觉计算机视觉
农业技术农业技术

背景情况:

为了根部细分,手工分析小米里希子图像 (MR) 是耗时的.
现有的语义细分方法通常在有限的,均的数据集上进行评估.
深度学习 (DL) 方法在准确性,错误阳性和可转移性方面存在有限的比较.

研究的目的:

为了比较六种最先进的DL方法用于语义根细分.
提出两个改进的DL模型,用于增强根细分.
在多样化和具有挑战性的MR数据集上评估模型性能和通用性.

主要方法:

六种已确定的DL语义细分技术的比较.
开发和评估两个新的DL模型,包括U-Net架构.
对同质 (玉米) 和异质 (混合物种,土壤类型,成像系统) 的MR数据集进行测试.
评估数据增强对模型性能的影响.
在独立的,未见的数据集上验证模型通用性的验证.

主要成果:

U-Net 模型表现出卓越的性能,编码器复杂度增加与更好的准确性和通用性相关.
非U-Net的方法在异质数据集方面遇到了困难.
数据增强显著改善了模型性能.
改进的深度元架构和特征提取器减少了假阳性.

结论:

神经网络架构大大减少了从MRI图像中计算根长度所需的时间.
复杂的架构显示出在现实世界MR图像分析中更高的细分精度和通用性的潜力.
未来的工作可以专注于文物处理,以尽量减少对模型再培训的需求.

关键词:

自动图像细分自动图像细分数据增强数据增强深度学习是一种深度学习.这是错误的阳性结果.很好的根,很好的根.图像处理图像处理矿物质中子 (MiniHirizotron) 是一种微小的物质.神经网络的神经网络的神经网络根部细分根部细分根部细分这就是U-Net.

更多相关视频

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data

Published on: April 26, 2016

An Optimized Rhizobox Protocol to Visualize Root Growth and Responsiveness to Localized Nutrients

An Optimized Rhizobox Protocol to Visualize Root Growth and Responsiveness to Localized Nutrients

Published on: October 22, 2018

相关概念视频

Basic Plant Anatomy: Roots, Stems, and Leaves

Basic Plant Anatomy: Roots, Stems, and Leaves

The primary organs of vascular plants are roots, stems, and leaves, but these structures can be highly variable, adapted for the specific needs and environment of different plant species.

Water and Mineral Acquisition

Water and Mineral Acquisition

Specialized tissues in plant roots have evolved to capture water, minerals, and some ions from the soil. Roots exhibit a variety of branching patterns that facilitate this process. The outermost root cells have specialized structures called root hairs that increase the root surface, thus increasing soil contact. Water can passively cross into roots, as the concentration of water in the soil is higher than that of the root tissue. Minerals, in contrast, are actively transported into root cells.

Photoreceptors and Plant Responses to Light

Photoreceptors and Plant Responses to Light

Light plays a significant role in regulating the growth and development of plants. In addition to providing energy for photosynthesis, light provides other important cues to regulate a range of developmental and physiological responses in plants.