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

Narcolepsy01:07

Narcolepsy

88
Narcolepsy is a chronic sleep disorder characterized by pervasive, uncontrolled sleepiness and other sleep disturbances. One of its hallmark symptoms is an abrupt transition to REM sleep upon falling asleep, which causes symptoms typically associated with this phase to occur unexpectedly during wakefulness. These include the following symptoms, which typically last from a minute or two to half an hour.
88

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

Bidirectional multi-nodes quantum teleportation using discrete-time quantum walk.

Scientific reports·2025
Same author

FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment.

PloS one·2025
Same author

Federated Reinforcement Learning-Based Dynamic Resource Allocation and Task Scheduling in Edge for IoT Applications.

Sensors (Basel, Switzerland)·2025
Same author

Free vibration characteristics of trapezoidal nanoplate rested on viscoelastic substrate with arbitrary boundary conditions using differential quadrature method.

PloS one·2025
Same author

Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions.

Sensors (Basel, Switzerland)·2025
Same author

Deep CNN-based detection of cardiac rhythm disorders using PPG signals from wearable devices.

PloS one·2025
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: May 28, 2025

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

实时驾驶员昏昏欲睡检测使用面部分析和机器学习技术.

Siham Essahraui1, Ismail Lamaakal1, Ikhlas El Hamly1

  • 1Multidisciplinary Faculty of Nador, Mohammed Premier University, Oujda 60000, Morocco.

Sensors (Basel, Switzerland)
|February 13, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了使用面部分析和机器学习的实时,非侵入性驾驶员昏昏欲睡检测系统. 像YOLOv5和YOLOv8这样的先进计算机视觉模型实现了卓越的性能,提高了道路安全.

关键词:
计算机视觉 计算机视觉昏昏欲睡的检测检测 昏昏欲睡的检测昏昏欲睡的驾驶情况面部分析 面部分析机器学习是机器学习.

更多相关视频

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
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

692

相关实验视频

Last Updated: May 28, 2025

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
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
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

692

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 道路安全工程 道路安全工程

背景情况:

  • 昏昏欲睡的驾驶是全球主要的道路安全问题,导致许多事故和死亡.
  • 现有的驾驶员昏昏欲睡检测 (DDD) 系统经常受到侵入性和缓慢响应时间的影响.

研究的目的:

  • 开发和评估一个实时,非侵入性的驾驶员昏昏欲睡的检测系统.
  • 系统地评估各种机器和深度学习算法对DDD性能.

主要方法:

  • 利用面部分析和机器学习技术来检测昏昏欲睡.
  • 评估K-最近邻居 (KNN),支持向量机器 (SVM),卷积神经网络 (CNN) 和先进的计算机视觉 (CV) 模型 (YOLOv5,YOLOv8,更快的R-CNN).
  • 在NTHUDDD,YawDD和UTA-RLDD公共数据集上测试了算法.

主要成果:

  • 在UTA-RLDD上,KNN实现了98.89%的准确性,99.27%的精度和98.86%的F1得分.
  • 在UTA-RLDD上,YOLOv5和YOLOv8表现出100%的精度和回忆率为99.5%mAP@0.5.
  • 更快的R-CNN在UTA-RLDD上显示出较低的性能,准确率为81.0%,精度为63.4%.

结论:

  • 先进的CV模型,特别是YOLOv5和YOLOv8,显示出对高精度,实时驾驶员昏昏欲睡的检测有很大的希望.
  • 开发的系统有潜力通过主动的实时警报大大提高道路安全.