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

Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...

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

Kaposiform hemangioendothelioma: Diagnosis and treatment.

Pediatric investigation·2026
Same author

Flame-Retardant Quasi-Solid-State Electrolytes From Self-Assembled Azolate Hybrid Frameworks for Highly Safe Lithium Batteries.

Angewandte Chemie (International ed. in English)·2026
Same author

Comparative analysis of the fine molecular structures and pasting properties of zhiqu and bread wheat starch.

Food chemistry: X·2026
Same author

Coordinated Bone-Muscle Axis Association in South China Carp (<i>Cyprinus carpio rubrofuscus</i>) with Low Bone Mineral Density: An Integrated Analysis of Muscle Texture, Nutrition, Ultrastructure, and Proteomics.

Foods (Basel, Switzerland)·2026
Same author

Skeletal Softening in <i>Cyprinus carpio rubrofuscus</i>: Insights from Mineral Metabolism, Histology, and Autophagy.

Animals : an open access journal from MDPI·2026
Same author

Prenatal diisononyl phthalate exposure induces the development of pulmonary dysplasia in offspring.

Scientific reports·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jun 29, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

1.5K

一个空间时间多功能网络 (STMF-Net) 用于基于骨架的建筑工人行动识别.

Yuanyuan Tian1, Sen Lin2, Hejun Xu3

  • 1School of Civil Engineering and Architecture, Wuyi University, Jiangmen 529020, China.

Sensors (Basel, Switzerland)
|December 17, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的深度学习模型,用于使用3D骨架数据识别建筑工人的行为. 空间时间多功能网络 (STMF-Net) 改善了工作现场的安全和效率监测.

关键词:
一个3D骨架.行动认可 行动认可建筑工人 建筑工人深度学习算法深度学习算法

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

466
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K

相关实验视频

Last Updated: Jun 29, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

1.5K
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

466
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K

科学领域:

  • 建设管理建设管理.
  • 人工智能的人工智能
  • 人与计算机的交互

背景情况:

  • 监测建筑工人的生产力,健康和安全是全球关注的问题.
  • 现有的动作识别方法通常依赖于单流数据,限制了特征捕获.
  • 位置估计和深度学习的进步为自动化工人行动评估提供了潜力.

研究的目的:

  • 开发一种有效的方法,以持续监测和及时识别建筑工人的行动.
  • 解决先前的行动识别研究中单一数据流的局限性.
  • 提出一种新的深度学习模型,用于加强员工行动评估.

主要方法:

  • 利用建筑工地3D骨架和关节轨迹数据.
  • 开发了一个时空多功能网络 (STMF-Net).
  • 包含六种类型的基于3D骨架的功能,用于全面的运动捕捉.

主要成果:

  • 在识别建筑工人的行为方面,STMF-Net的准确率达到了79.36%.
  • 该模型有效地捕获和处理多功能3D骨架数据.
  • 证明了深度学习对于强大的劳动力行动评估的能力.

结论:

  • 拟议的STMF-Net提高了监控和识别建筑工人的行动的能力.
  • 这项技术有可能改善建筑行业的管理模式.
  • 最终,这项研究的目的是通过先进的监测来提高工人健康和工作效率.