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Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems

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Cover of 'Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Multi-modal Emotion Feature Extraction
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    Chapter 3 Deep Sparse Autoencoder Network for Facial Emotion Recognition
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    Chapter 4 AdaBoost-KNN with Direct Optimization for Dynamic Emotion Recognition
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    Chapter 5 Weight-Adapted Convolution Neural Network for Facial Expression Recognition
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    Chapter 6 Two-Layer Fuzzy Multiple Random Forest for Speech Emotion Recognition
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    Chapter 7 Two-Stage Fuzzy Fusion Based-Convolution Neural Network for Dynamic Emotion Recognition
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    Chapter 8 Multi-support Vector Machine Based Dempster-Shafer Theory for Gesture Intention Understanding
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    Chapter 9 Three-Layer Weighted Fuzzy Support Vector Regressions for Emotional Intention Understanding
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    Chapter 10 Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Model
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    Chapter 11 Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression
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    Chapter 12 Emotional Human-Robot Interaction Systems
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    Chapter 13 Experiments and Applications of Emotional Human-Robot Interaction Systems
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    Chapter 14 Correction to: Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Model
Attention for Chapter 6: Two-Layer Fuzzy Multiple Random Forest for Speech Emotion Recognition
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Citations

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4 Mendeley
Summary Dimensions citations
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Chapter title
Two-Layer Fuzzy Multiple Random Forest for Speech Emotion Recognition
Chapter number 6
Book title
Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems
Published by
Springer, Cham, November 2020
DOI 10.1007/978-3-030-61577-2_6
Book ISBNs
978-3-03-061576-5, 978-3-03-061577-2
Authors

Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota, Chen, Luefeng, Wu, Min, Pedrycz, Witold, Hirota, Kaoru

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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 %
Student > Bachelor 1 25%
Student > Postgraduate 1 25%
Unknown 2 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 25%
Computer Science 1 25%
Unknown 2 50%

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