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

Microcracking in Concrete01:20

Microcracking in Concrete

115
Microcracking in concrete refers to the tiny cracks that can form within the material even before any external load is applied. These microcracks typically occur at the interface between the coarse aggregate and the hydrated cement paste, often as a result of differential volume changes prompted by variations in stress-strain behavior, as well as thermal and moisture movement. Initially, these microcracks remain stable and do not grow substantially until the concrete is stressed to about 30...
115
Segregation in Fresh Concrete01:16

Segregation in Fresh Concrete

108
Segregation in fresh concrete is a phenomenon where the components of the concrete mix separate, leading to uneven distribution and compromised structural integrity. This separation typically occurs when concrete is subjected to excessive horizontal movement within forms, or when it is dropped from considerable heights or forced through narrow, winding paths. As a result, heavier coarse aggregate particles settle at the bottom, while lighter, finer materials such as cement and water rise to the...
108
Types of Non-structural Cracks in Concrete01:28

Types of Non-structural Cracks in Concrete

140
Non-structural cracks are primarily of three types: plastic, early-age thermal, and drying shrinkage cracks. Plastic cracks are further classified into plastic shrinkage cracks and plastic settlement cracks.
Plastic shrinkage cracks typically form within hours after the concrete is poured. The concrete's surface dries faster than the bottom, creating tensile stress that the still-plastic concrete cannot withstand, leading to diagonal or randomly patterned cracks on the concrete surface.
140

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

Genetic variation in an miRNA-1827 binding site in MYCL1 alters susceptibility to small-cell lung cancer.

Cancer research·2011
Same author

Effects of electrode surface modification with chlorotoxin on patterning single glioma cells.

Physical chemistry chemical physics : PCCP·2011
Same author

Intracranial clear cell meningioma: a clinicopathologic study of 15 cases.

Acta neurochirurgica·2011
Same author

Striatal-enriched protein tyrosine phosphatase expression and activity in Huntington's disease: a STEP in the resistance to excitotoxicity.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2011
Same author

1-(4,5-Dinitro-10-aza-tricyclo-[6.3.1.0]dodeca-2,4,6-trien-10-yl)-2,2,2-trifluoro-ethanone.

Acta crystallographica. Section E, Structure reports online·2011
Same author

1,2,3,4-Tetra-hydro-1,4-methano-naphthalene-2,3-diol.

Acta crystallographica. Section E, Structure reports online·2011

相关实验视频

Updated: Jun 21, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.0K

一个用于道路裂的语义细分模型,它结合了通道空间卷积和频率特征聚合.

Mingxing Zhang1, Jian Xu2

  • 1School of Electronics and information, Xi'an Polytechnic University, Xi'an, 710048, China. zmx18792354440@163.com.

Scientific reports
|July 11, 2024
PubMed
概括

本研究引入了一种新的语义细分模型,以使用组合道空间卷积和频率特征准确检测道路裂. 改进的模型通过精确识别复杂背景中的裂来提高道路安全.

科学领域:

  • 土木工程 土木工程是指土木工程.
  • 计算机视觉 计算机视觉
  • 图像处理 图像处理

背景情况:

  • 道路裂在运输基础设施中构成重大安全风险.
  • 现有的语义细分模型因捕捉空间-通道关系和复杂背景的挑战而难以检测裂纹.

研究的目的:

  • 为准确的道路裂检测提出一个先进的语义细分模型.
  • 解决当前模型关于空间通道特征合和背景差异化的局限性.

主要方法:

  • 开发了一种新的卷积块,集成道空间卷积,用于增强像素识别.
  • 引入了一个频域特征聚合模块,以改善裂纹边缘对比度.
  • 整合了一个功能改进模块,以提高细分精度.

主要成果:

  • 与流行的通用型号相比,拟议的模型表现出优越的性能.
  • 实验结果验证了该模型在识别道路裂方面的有效性.

结论:

  • 新的语义细分模型为道路裂检测提供了更好的准确性和应用潜力.
  • 这项研究通过先进的图像分析技术,有助于提高道路安全.
关键词:
深度学习是一种深度学习.频率特征聚合频率特征聚合图像细分,神经网络,神经网络道路裂检测 道路裂检测

更多相关视频

Advanced Self-Healing Asphalt Reinforced by Graphene Structures: An Atomistic Insight
08:03

Advanced Self-Healing Asphalt Reinforced by Graphene Structures: An Atomistic Insight

Published on: May 31, 2022

4.5K
Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation
04:58

Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation

Published on: January 6, 2023

2.2K

相关实验视频

Last Updated: Jun 21, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.0K
Advanced Self-Healing Asphalt Reinforced by Graphene Structures: An Atomistic Insight
08:03

Advanced Self-Healing Asphalt Reinforced by Graphene Structures: An Atomistic Insight

Published on: May 31, 2022

4.5K
Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation
04:58

Mechanoluminescent Visualization of Crack Propagation for Joint Evaluation

Published on: January 6, 2023

2.2K