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Human Activity Sensing

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Cover of 'Human Activity Sensing'

Table of Contents

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    Book Overview
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    Chapter 1 Optimizing of the Number and Placements of Wearable IMUs for Automatic Rehabilitation Recording
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    Chapter 2 Identifying Sensors via Statistical Analysis of Body-Worn Inertial Sensor Data
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    Chapter 3 Compensation Scheme for PDR Using Component-Wise Error Models
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    Chapter 4 Towards the Design and Evaluation of Robust Audio-Sensing Systems
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    Chapter 5 A Wi-Fi Positioning Method Considering Radio Attenuation of Human Body
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    Chapter 6 Drinking Gesture Recognition from Poorly Annotated Data: A Case Study
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    Chapter 7 Understanding How Non-experts Collect and Annotate Activity Data
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    Chapter 8 A Multi-media Exchange Format for Time-Series Dataset Curation
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    Chapter 9 OpenHAR: A Matlab Toolbox for Easy Access to Publicly Open Human Activity Data Sets—Introduction and Experimental Results
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    Chapter 10 MEASURed: Evaluating Sensor-Based Activity Recognition Scenarios by Simulating Accelerometer Measures from Motion Capture
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    Chapter 11 Benchmark Performance for the Sussex-Huawei Locomotion and Transportation Recognition Challenge 2018
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    Chapter 12 Bayesian Optimization of Neural Architectures for Human Activity Recognition
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    Chapter 13 Into the Wild—Avoiding Pitfalls in the Evaluation of Travel Activity Classifiers
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    Chapter 14 Effects of Activity Recognition Window Size and Time Stabilization in the SHL Recognition Challenge
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    Chapter 15 Winning the Sussex-Huawei Locomotion-Transportation Recognition Challenge
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Title
Human Activity Sensing
Published by
Springer International Publishing, October 2019
DOI 10.1007/978-3-030-13001-5
ISBNs
978-3-03-013000-8, 978-3-03-013001-5
Editors

Kawaguchi, Nobuo, Nishio, Nobuhiko, Roggen, Daniel, Inoue, Sozo, Pirttikangas, Susanna, Van Laerhoven, Kristof

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 25%
Student > Doctoral Student 1 13%
Student > Ph. D. Student 1 13%
Student > Master 1 13%
Professor > Associate Professor 1 13%
Other 0 0%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 3 38%
Engineering 2 25%
Agricultural and Biological Sciences 1 13%
Unknown 2 25%