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In-Vehicle Corpus and Signal Processing for Driver Behavior

Overview of attention for book
Cover of 'In-Vehicle Corpus and Signal Processing for Driver Behavior'

Table of Contents

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    Book Overview
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    Chapter 1 Improved Vehicle Safety and How Technology Will Get Us There, Hopefully
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    Chapter 2 New Concepts on Safe Driver-Assistance Systems
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    Chapter 3 Real-World Data Collection with “UYANIK”
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    Chapter 4 On-Going Data Collection of Driving Behavior Signals
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    Chapter 5 UTDrive: The Smart Vehicle Project
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    Chapter 6 Wireless Lan-Based Vehicular Location Information Processing
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    Chapter 7 Perceptually Optimized Packet Scheduling for Robust Real-Time Intervehicle Video Communications
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    Chapter 8 Machine Learning Systems for Detecting Driver Drowsiness
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    Chapter 9 Extraction of Pedestrian Regions Using Histogram and Locally Estimated Feature Distribution
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    Chapter 10 EEG Emotion Recognition System
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    Chapter 11 Three-Dimensional Ultrasound Imaging in Air for Parking and Pedestrian Protection
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    Chapter 12 A New Method for Evaluating Mental Work Load In n-Back Tasks
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    Chapter 13 Estimation of Acoustic Microphone Vocal Tract Parameters from Throat Microphone Recordings
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    Chapter 14 Cross-Probability Model Based on Gmm for Feature Vector Normalization
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    Chapter 15 Robust Feature Combination for Speech Recognition Using Linear Microphone Array in a Car
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    Chapter 16 Prediction of Driving Actions from Driving Signals
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    Chapter 17 Design of Audio-Visual Interface for Aiding Driver’s Voice Commands in Automotive Environment
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    Chapter 18 Estimation of High-Variance Vehicular Noise
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    Chapter 19 Feature Compensation Employing Model Combination for Robust In-Vehicle Speech Recognition
Attention for Chapter 6: Wireless Lan-Based Vehicular Location Information Processing
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Citations

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Summary Dimensions citations
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Chapter title
Wireless Lan-Based Vehicular Location Information Processing
Chapter number 6
Book title
In-Vehicle Corpus and Signal Processing for Driver Behavior
Published by
Springer US, October 2008
DOI 10.1007/978-0-387-79582-9_6
Book ISBNs
978-0-387-79581-2, 978-0-387-79582-9
Authors

Seigo Ito, Nobuo Kawaguchi

Editors

Kazuya Takeda, Hakan Erdogan, John H. L. Hansen, Huseyin Abut

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 25%
Researcher 1 25%
Other 1 25%
Student > Master 1 25%
Readers by discipline Count As %
Computer Science 3 75%
Engineering 1 25%

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