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

What are Viruses?00:50

What are Viruses?

Overview
Mismatch Repair01:20

Mismatch Repair

Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
Defense Mechanism Against Infection01:26

Defense Mechanism Against Infection

Natural flora, body system defenses, and inflammation are natural barriers of the body against infectious agents regardless of previous exposure. Normal floras of the human body refer to the microbial population that colonizes the skin and mucous membranes.
In addition, many body organ systems have unique defenses against infection. The skin is an intact, multilayered surface preventing invasion by microorganisms unless impaired. Mucous membranes lining the mouth, nose, and eyelids are barriers...
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Viruses with RNA Genomes01:29

Viruses with RNA Genomes

RNA viruses are categorized into positive-strand, negative-strand, or double-stranded groups based on their genomic structure and replication mechanisms. This classification dictates how they exploit host cellular machinery for protein synthesis and replication. Some RNA viruses also utilize reverse transcription as part of their life cycle, further diversifying their replication strategies.Positive-Strand RNA VirusesPositive-strand RNA viruses have genomes that function directly as messenger...
Transmission of Pathogens01:24

Transmission of Pathogens

Pathogens spread from their reservoirs to susceptible hosts through three main routes: contact transmission, vehicle transmission, and vector transmission. Each route involves distinct mechanisms of transfer.Contact TransmissionThis category includes direct contact, indirect contact, and droplet transmission:Direct contact involves immediate physical interaction between individuals—such as a handshake—which can spread pathogens like Streptococcus pyogenes, the bacterium responsible for...

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

Real-World Outcomes of Switching to Aflibercept 8 mg in Previously Treated Neovascular Age-Related Macular Degeneration: A Systematic Review and Meta-Analysis.

Journal of clinical medicine·2026
Same author

Monitoring land degradation by soil salinity using Sentinel-2 satellite data and GIS techniques: A case study of Sabkhat Ghuwaymid, Saudi Arabia.

PloS one·2026
Same author

Clinical Outcomes of High-Dose Aflibercept 8 mg in Polypoidal Choroidal Vasculopathy: A Systematic Review and Meta-Analysis.

Cureus·2026
Same author

Demystifying Artificial Intelligence: A Systematic Review of Explainable Artificial Intelligence in Medical Imaging.

Sensors (Basel, Switzerland)·2026
Same author

LADNET: An MRI-based deep learning approach for Alzheimer's disease detection.

Computers in biology and medicine·2026
Same author

Retinal and Choroidal Structural and Microvascular Characteristics in Women With Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis of Optical Coherence Tomography (OCT) and OCT Angiography (OCTA) Studies.

Cureus·2026

相关实验视频

Updated: Jul 2, 2026

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

680

使用轻量级修改软注意网络检测麻病.

Arailym Dosset1, L Minh Dang2,3,4, Faisal Alharbi5

  • 1Department of Computer Science and Engineering, Sejong University, Seoul, Republic of Korea.

Pest management science
|October 21, 2024
PubMed
概括

早期发现麻瓜疾病对于作物产量至关重要. 一个新的轻量级框架,CDDNet,使用MobileNetV3Small和注意力机制,在边缘设备上准确地实时识别麻病.

关键词:
发现麻瓜病的检测方法农作物 农作物 农作物深度学习是一种深度学习.轻量级网络轻量级的网络.修改了注意力的注意力.害虫控制 害虫控制 害虫控制 害虫控制

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

475
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K

相关实验视频

Last Updated: Jul 2, 2026

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

680
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

475
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K

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:

  • 大麻作物容易受到病毒感染的影响,影响产量和质量.
  • 手动识别疾病是耗时的,需要专家知识.
  • 需要对边缘设备进行高效,轻量级的疾病检测.

研究的目的:

  • 引入CDDNet,一个高效和轻量级的框架,用于早期检测麻病.
  • 为了利用MobileNetV3Small进行优化功能提取.
  • 通过修改软注意模块来增强疾病区域优先级.

主要方法:

  • 使用MobileNetV3Small作为功能提取的骨干.
  • 实施了修改后的软注意力机制,以专注于患病的植物区域.
  • 在疾病发展的早期和中期阶段验证的特征.

主要成果:

  • 实现了高精度:98.95% (CID),97.03% (CPDM) 和98.25% (CPCD) 的精度.
  • 在准确性,参数数量和FPS方面,CDDNet超过了最先进的方法.
  • 在实时检测麻疾病方面表现出卓越的性能.

结论:

  • 轻量化和高效的技术对于实时管理麻病至关重要.
  • 修改软注意力显著改善模型在疾病检测中的性能.
  • CDDNet提供了一个实用的解决方案,用于早期麻病的疾病分类.