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Titlebook: In-Vehicle Corpus and Signal Processing for Driver Behavior; Kazuya Takeda,John H. L. Hansen,Hüseyin Abut Book 2009 Springer-Verlag US 200

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发表于 2025-3-21 18:23:19 | 显示全部楼层 |阅读模式
书目名称In-Vehicle Corpus and Signal Processing for Driver Behavior
编辑Kazuya Takeda,John H. L. Hansen,Hüseyin Abut
视频video
概述Comprised of the best papers of DSPinCARS 2007.Presents the latest advances in in-vehicle technology.Includes supplementary material:
图书封面Titlebook: In-Vehicle Corpus and Signal Processing for Driver Behavior;  Kazuya Takeda,John H. L. Hansen,Hüseyin Abut Book 2009 Springer-Verlag US 200
描述.In-Vehicle Corpus and Signal Processing for Driver Behavior. is comprised of expanded papers from the third biennial DSPinCARS held in Istanbul in June 2007. The goal is to bring together scholars working on the latest techniques, standards, and emerging deployment on this central field of living at the age of wireless communications, smart vehicles, and human-machine-assisted safer and comfortable driving. Topics covered in this book include: improved vehicle safety; safe driver assistance systems; smart vehicles; wireless LAN-based vehicular location information processing; EEG emotion recognition systems; and new methods for predicting driving actions using driving signals...In-Vehicle Corpus and Signal Processing for Driver Behavior. is appropriate for researchers, engineers, and professionals working in signal processing technologies, next generation vehicle design, and networks for mobile platforms..
出版日期Book 2009
关键词Automobil; DSP; Information; Standards; communication; corpus; driver behavior; in-vehicle; platform; safety;
版次1
doihttps://doi.org/10.1007/978-0-387-79582-9
isbn_softcover978-1-4419-4640-9
isbn_ebook978-0-387-79582-9
copyrightSpringer-Verlag US 2009
The information of publication is updating

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Wireless Lan-Based Vehicular Location Information Processing, difference in signal strength distribution according to the location of wireless LAN antenna. By using these differences we can estimate vehicles’ orientation. Finally, we introduce our metropolitan-scale localization project named Locky.jp.
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UTDrive: The Smart Vehicle Project,d). Here, we describe our in-vehicle data collection framework, data collection protocol, dialog and secondary task demands, data analysis, and preliminary experimental results. Finally, we discuss our proposed multi-layer data transcription procedure for in-vehicle data collection and future research directions.
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