Jove
Visualize
联系我们
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

相关概念视频

Light Acquisition02:16

Light Acquisition

8.4K
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.
8.4K

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

A minimal-net CNN model for an IoT-based brain tumor detection and monitoring system.

Scientific reports·2026
Same author

A novel qVGG-4 model for optimizing a parameterized quantum circuit in a quantum-IoT-based brain tumor detection and monitoring system.

Computer methods and programs in biomedicine·2026
Same author

BrainFusionNet: a deep learning and XAI model to understand local, global, and sequential features of MRI images for improved brain tumour detection.

Brain informatics·2026
Same author

A lightweight convolutional neural network for real-time monitoring of smart mango orchard systems.

Scientific reports·2026
Same author

LBNet: an optimized lightweight CNN for mammographic breast cancer classification with XAI-based interpretability.

Scientific reports·2025
Same author

Mental Health Diagnosis From Voice Data Using Convolutional Neural Networks and Vision Transformers.

Journal of voice : official journal of the Voice Foundation·2024

相关实验视频

Updated: Jun 18, 2025

Specific and Accurate Detection of the Citrus Greening Pathogen Candidatus liberibacter spp. Using Conventional PCR on Citrus Leaf Tissue Samples
09:23

Specific and Accurate Detection of the Citrus Greening Pathogen Candidatus liberibacter spp. Using Conventional PCR on Citrus Leaf Tissue Samples

Published on: June 29, 2018

7.6K

多格式开源甜叶数据集用于疾病检测,分类和分析.

Yousuf Rayhan Emon1, Md Taimur Ahad1, Golam Rabbany1

  • 1Daffodil International University, Daffodil Smart City (DSC), Birulia, Savar, Dhaka 1216, Bangladesh.

Data in brief
|August 5, 2024
PubMed
概括

为了改善水果生产,创建了孟加拉国甜病的新数据集. 这种机器学习数据集有助于早期发现和分类疾病,有利于农民和农业工程研究.

科学领域:

  • 农业科学 农业科学
  • 计算机视觉 计算机视觉
  • 机器学习 机器学习

背景情况:

  • 在孟加拉国,甜种植在经济上很重要,但疾病爆发显著降低了水果产量.
  • 现有的机器学习 (ML) 数据集用于果病诊断是不够的,特别是在孟加拉国发现的地区特定变异方面.
  • 使用ML模型的计算机辅助诊断为准确及及时检测甜病提供了一个有希望的解决方案.

研究的目的:

  • 开发一个全面的,高质量的数据集,关于孟加拉国特有的甜植物疾病.
  • 促进机器学习和计算机视觉技术的应用,用于识别和分类甜的疾病.
  • 支持农业工程的进步,并为农民提供减轻作物损失的工具.

主要方法:

  • 在八月份收集了甜植物的高分辨率图像数据集.
  • 数据集包括各种疾病状况,如类癌症,类绿化,死退,粉,黄叶和健康样本.
  • 确保数据集格式适合各种机器学习算法要求.

主要成果:

  • 一个关于孟加拉国甜病的新型数据集已成功编制.
  • 该数据集捕捉了多种疾病类型和健康的叶子图像,对于训练诊断模型至关重要.
  • 为农业机器学习领域的研究人员和开发人员提供了宝贵的资源.
关键词:
计算机视觉 计算机视觉 计算机视觉深度学习是一种深度学习.疾病检测 检测 检测图像的分类图像的分类.机器学习是机器学习.植物病理学 植物病理学甜甜的子叶子

更多相关视频

Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

1.9K
Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

9.8K

相关实验视频

Last Updated: Jun 18, 2025

Specific and Accurate Detection of the Citrus Greening Pathogen Candidatus liberibacter spp. Using Conventional PCR on Citrus Leaf Tissue Samples
09:23

Specific and Accurate Detection of the Citrus Greening Pathogen Candidatus liberibacter spp. Using Conventional PCR on Citrus Leaf Tissue Samples

Published on: June 29, 2018

7.6K
Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

1.9K
Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

9.8K

结论:

  • 开发的数据集解决了孟加拉国甜病诊断现有资源的局限性.
  • 它可以开发和验证先进的ML模型,用于早期检测疾病,从而提高作物产量.
  • 这种资源可以帮助农民及时实施预防措施,从而减少经济损失并支持可持续的甜种植.