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西安交通大学 [13]
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北京航空航天大学 [1]
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期刊论文 [15]
会议论文 [13]
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Design and Evaluation of a Surface Electromyography-Controlled Steering Assistance Interface
期刊论文
SENSORS, 2019, 卷号: 19
作者:
Nacpil, Edric John Cruz
;
Wang, Zheng
;
Zheng, Rencheng
;
Kaizuka, Tsutomu
;
Nakano, Kimihiko
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2019/12/02
human-machine interface (HMI)
surface electromyography (sEMG)
advanced driver assistance system (ADAS)
automated driving
Methodologies for Evaluating and Optimizing Multimodal Human-Machine-Interface of Autonomous Vehicles
会议论文
作者:
Ge, Xinyu
;
Li, Xinyu
;
Wang, Ying
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/11/19
Automotive applications
Cost-effective solutions
Driving assistance systems
Human Machine Interface
Human-machine interface system
Learning neural networks
Multimodal communications
Original equipment manufacturers
Automatic Dangerous Driving Intensity Analysis for Advanced Driver Assistance Systems From Multimodal Driving Signals
期刊论文
IEEE SENSORS JOURNAL, 2018, 卷号: 18, 页码: 4785-4794
作者:
Yin, Jia-Li
;
Chen, Bo-Hao
;
Lai, Kuo-Hua Robert
;
Li, Ying
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2019/11/21
dangerous intensity
Driving behaviors
advanced driver assistance systems
A Platform Solution of Data-Quality Improvement for Internet-of-Vehicle Services
会议论文
2018 IEEE International Conference on Pervasive Computing and Communications, PerCom 2018
作者:
Zhang, M.
;
Wo, T.
;
Xie, T.
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/12/30
Data mining
Data reduction
Interpolation
Safety engineering
Ubiquitous computing
Vehicles
Web services
Data quality
Dependability
Driving assistance
Industrial systems
Internet-of-vehicles
Sequence matching
Transportation technology
Vehicle networkings
Big data
Curve speed model for driver assistance based on driving style classification
期刊论文
IET Intelligent Transport Systems, 2017, 卷号: 11, 期号: 8, 页码: 501-510
作者:
Chu, Duanfeng
;
Deng, Zejian
;
He, Yi
;
Wu, Chaozhong*
;
Sun, Chuan
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2019/12/04
pattern classification
pattern clustering
road safety
behavioural sciences
alarm systems
driver information systems
driver assistance
driving style classification
curve speed model
road factors
vehicle-road interaction model
driver behaviour factor
vehicle factors
fuzzy synthetic evaluation method
K-means clustering method
driving safety
road adhesion coefficient
lateral instability crashes
curve speed warning system
driving comfort
汽车经济性驾驶技术及应用概述
期刊论文
2016, 2016
李升波
;
徐少兵
;
王文军
;
成波
;
LI Shengbo
;
XU Shaobing
;
WANG Wenjun
;
CHENG Bo
收藏
  |  
浏览/下载:4/0
基于AIC信息量准则的车辆油耗建模与评估
期刊论文
2016, 2016
俞倩雯
;
李克强
;
Yu Qianwen
;
Li Keqiang
收藏
  |  
浏览/下载:3/0
基于图像行数据处理的车道偏离预警系统
期刊论文
2016, 2016
易世春
;
李克强
;
李防震
;
张强
;
Yi Shichun
;
Li Keqiang
;
Li Fangzhen
;
Zhang Qiang
收藏
  |  
浏览/下载:6/0
Driving posture recognition by convolutional neural networks
期刊论文
IET COMPUTER VISION, 2016, 卷号: 10, 期号: [db:dc_citation_issue], 页码: 103-114
作者:
Yan, Chao
;
Coenen, Frans
;
Zhang, Bailing
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2019/12/02
road conditions
driver information systems
unsupervised learning
effectiveness performance
sparse filtering
feature extraction
cell phone call
feedforward neural nets
image classification
traffic accidents
road traffic
video clips
road accidents
pose estimation
normal driving
intelligent driver assistance system development
poor illuminations
eating
driver fatigue
unsupervised feature learning method
smoking
image descriptors
embedded functionality
convolutional neural networks
driver hand position monitoring
automatic discriminative feature learning
object recognition
driving posture recognition
driver inattention
video signal processing
Southeast University driving posture dataset
image filtering
generalisation performance
driver vigilance monitoring
Driving posture recognition by convolutional neural networks
会议论文
作者:
Yan, Chao
;
Zhang, Bailing
;
Coenen, Frans
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2019/12/02
Convolutional neural network
Convolutional Neural Networks (CNN)
Discriminative features
Driver vigilance monitoring
Driving assistance systems
Driving posture
Intelligent driver assistance systems
Unsupervised feature learning
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