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

相关实验视频

Updated: May 15, 2025

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
07:15

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

4.4K

使用多式联络神经网络优化驾驶员疲劳检测方法.

Shengli Cao1, Peihua Feng2, Wei Kang3

  • 1School of Automation, Xi'an University of Posts and Telecommunications, Chang'an South Road, Xi'an, 710061, Shannxi, People's Republic of China.

Scientific reports
|April 10, 2025
PubMed
概括
此摘要是机器生成的。

相关概念视频

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

High mobility group box 1 (HMGB1) levels in the placenta and in serum in preeclampsia.

American journal of reproductive immunology (New York, N.Y. : 1989)·2011
Same author

Destabilization of coxsackievirus b3 genome integrated with enhanced green fluorescent protein gene.

Intervirology·2011
Same author

[Clinicopathological features of primary splenic histiocytic sarcoma: a case report and literature review].

Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi·2011
Same author

[Comparison of treatment with micro endoscopic discectomy and posterior lumbar interbody fusion using single and double B-Twin expandable spinal spacer].

Zhonghua wai ke za zhi [Chinese journal of surgery]·2011
Same author

Virtual transplantation in designing a facial prosthesis for extensive maxillofacial defects that cross the facial midline using computer-assisted technology.

The International journal of prosthodontics·2011
Same author

Total synthesis of phorboxazole A via de novo oxazole formation: convergent total synthesis.

Journal of the American Chemical Society·2010

一个新的多式联接神经网络模型使用生理和面部数据准确地检测驾驶员的疲劳. 这种先进的系统达到98.41%的准确性,通过可靠的监控显著提高了道路安全.

科学领域:

  • 人工智能的人工智能
  • 生物医学工程 生物医学工程
  • 运输安全运输安全

背景情况:

  • 驾驶员疲劳是道路交通事故的主要原因之一.
  • 目前的检测方法往往缺乏精度和可靠性.
  • 需要先进的系统来监测驾驶员的警觉性.

研究的目的:

  • 开发和评估一种新的多式联网神经网络,用于精确检测驾驶员疲劳.
  • 调查整合生理和面部数据的有效性.
  • 通过提供可靠的疲劳监测解决方案,提高道路安全.

主要方法:

  • 使用了包含生理 (EEG,ECG) 和面部数据的DROZY数据集.
  • 开发了两种多式联络神经网络模型:特征组合和特征合.
  • 亮点模型采用了复杂的合机制,其中特征相互权衡.

主要成果:

  • 多式联用模型实现了98.41%的准确率,98.38%的精度,98.39%的回忆率和98.38%的F1分数.
  • 多式联运功能组合模型实现了94.87%的准确性.
  • 多数投票策略提高了决策的稳定性.
关键词:
司机疲劳导致的疲劳功能组合的功能组合.多模式功能合模式的多模式功能道路交通安全问题 道路安全问题

更多相关视频

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K
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

2.5K

相关实验视频

Last Updated: May 15, 2025

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research
07:15

Tactile Vibrating Toolkit and Driving Simulation Platform for Driving-Related Research

Published on: December 18, 2020

4.4K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K
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

2.5K

结论:

  • 这款多式联动型车型在驾驶员疲劳检测方面表现出卓越的性能.
  • 这种方法为车载监控系统带来了重大进步.
  • 这些发现有助于制定更有效的策略来预防与疲劳有关的事故.