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

Generation of Action Potential in Skeletal Muscles01:24

Generation of Action Potential in Skeletal Muscles

4.6K
Every cell in the body maintains a membrane potential due to an uneven distribution of positive and negative charges across its plasma membrane. The membrane potential is measured in millivolts and quantifies the difference in charge across the membrane.
Like neurons, muscle cells are also regarded as excitable due to their capacity to change in response to stimuli, primarily due to voltage-gated ion channels embedded in their plasma membranes, which get activated by alterations in the...
4.6K
Muscle Coordination and Action01:24

Muscle Coordination and Action

1.6K
Muscle coordination is a complex and finely tuned process essential for smooth and purposeful movements like flexion, extension, adduction, abduction, and rotation. The human body orchestrates the actions of various muscles working in concert, each with a specific role. Four functional types describe how muscles work together: agonist, antagonist, synergist, and fixator.
Agonists
Agonist muscles, often called prime movers, are the primary muscles responsible for producing a specific movement....
1.6K
Classification of Bones01:18

Classification of Bones

5.7K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
5.7K
Structural Classification of Joints01:20

Structural Classification of Joints

3.5K
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...
3.5K
Carbon Skeletons01:12

Carbon Skeletons

107.8K
Life on Earth is carbon-based, as all macromolecules that make up living organisms contain carbon atoms. All organic compounds have a carbon backbone. Each carbon atom is tetravalent and can bond with four other atoms, making it an extraordinarily flexible component of biological molecules. Because carbon’s valence electrons are stable, it rarely becomes an ion. As the carbon chain increases in length, structural modifications such as ring structures, double bonds, and branching side...
107.8K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

123
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
123

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

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Robust point cloud registration based on semantic iterative closest point algorithm.

Fundamental research·2026
Same author

AsyCMST: Asymmetric cross-modal spatio-temporal learning for multimodal ultrasound nodule recognition.

Medical image analysis·2026
Same author

Hyper-RAG: combating LLM hallucinations using hypergraph-driven retrieval-augmented generation.

Nature communications·2026
Same author

TSFA: A Two-Stage Feature Alignment Method for Unsupervised Open-Set Domain Adaptation in Time-Series Classification.

IEEE transactions on neural networks and learning systems·2026
Same author

SCADA: Sparse cross attention for domain adaptive semantic segmentation.

Neural networks : the official journal of the International Neural Network Society·2026

相关实验视频

Updated: Jul 16, 2025

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

1.6K

见和关注:全球和地方规模的图形卷积网络,用于基于骨架的动作识别.

Xuehao Gao1, Shaoyi Du1, Yang Yang2

  • 1Institute of Artificial Intelligence and Robotics, National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi'an Jiaotong University, Xi'an, 710049, Shanxi, China.

Neural networks : the official journal of the International Neural Network Society
|September 11, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了基于3D骨架的动作识别的新方法,增强了空间和时间运动模式的学习. 该方法改进了特征提取,以便更准确地分析人类姿势和轨迹.

关键词:
全球和地方规模的图表图表.图形卷积网络中的图形卷积网络.基于骨架的行动识别.

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

568
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K

相关实验视频

Last Updated: Jul 16, 2025

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

1.6K
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

568
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K

科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 人与计算机的交互

背景情况:

  • 基于3D骨的动作识别对于理解人类行为至关重要.
  • 从骨架数据中学习有效的空间和时间运动模式仍然具有挑战性.

研究的目的:

  • 开发用于捕捉多范围姿势特征和丰富时间轨迹特征的改进方法.
  • 为了提高基于骨架的动作识别系统的准确性和稳定性.

主要方法:

  • 一个新的见焦点动作识别策略,用于联合姿势特征提取.
  • 一个时间特征提取器 (JD-TC) 通过建模框架间的相关性来丰富轨迹特征.
  • 将这些方法结合起来,创建一个全面的基于骨架的动作识别系统.

主要成果:

  • 拟议的系统有效地从骨序列中提取丰富的姿势和轨迹特征.
  • 该方法在三个大规模数据集上显著优于以前的最先进方法.
  • 在基于3D骨架的动作识别任务中表现出卓越的性能.

结论:

  • 结合的见焦点策略和JD-TC提取器为基于骨架的动作识别提供了强大的解决方案.
  • 这项工作通过解决空间和时间特征学习中未被探索的问题来推动该领域的进步.
  • 开发的系统为使用骨架数据的动作识别提供了一个新的基准.