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相关概念视频

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

125
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...
125

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相关实验视频

Updated: Jul 25, 2025

Paw-Print Analysis of Contrast-Enhanced Recordings PrAnCER: A Low-Cost, Open-Access Automated Gait Analysis System for Assessing Motor Deficits
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区域时间序列编码网络和多视图图像生成网络用于短期步行识别.

Wenhao Sun1,2, Guangda Lu1,2, Zhuangzhuang Zhao1,2

  • 1School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China.

Entropy (Basel, Switzerland)
|June 28, 2023
PubMed
概括

这项研究引入了一种新的步态识别网络,可以生成交叉视图步态数据并提取运动特征. 该方法有效地从短步视频中识别个人,增强生物识别身份验证.

关键词:
功能融合功能融合功能图像生成网络 图像生成网络短时间的步态识别.时间序列的特征提取.

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Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
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科学领域:

  • 生物识别身份验证
  • 计算机视觉 计算机视觉
  • 人类运动分析分析

背景情况:

  • 步态识别对生物识别至关重要,但由于短数据和视图变化而受到阻碍.
  • 现有的方法与不完整的步态序列和交叉视图不一致性作斗争.

研究的目的:

  • 开发一种步态识别系统,克服短数据和交叉视图变化的局限性.
  • 通过使用新的特征提取技术,提高步态识别的准确性和稳定性.

主要方法:

  • 一个步态数据生成网络扩展了跨视图步态轮数据.
  • 一个步行运动特征提取网络使用区域时间序列编码进行联合运动分析.
  • 双线矩阵分解聚合保险丝轮和运动特征.

主要成果:

  • 拟议的网络有效地扩展了多视图步态数据,并提取了人类运动时间序列特征.
  • 在OUMVLP-Pose和CASIA-B数据集上的验证证明了使用Rank-1准确度等指标的网络有效性.
  • 现实世界的测试证实了该方法在短时间视频步行识别方面的可行性和有效性.

结论:

  • 开发的双分支融合网络从短视频输入中实现了完全的步态识别.
  • 该方法成功地解决了步态识别方面的挑战,提供了强大且可行的解决方案.