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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction

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Cover of 'Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction'

Table of Contents

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    Book Overview
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    Chapter 1 Active Shape Model vs. Deep Learning for Facial Emotion Recognition in Security
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    Chapter 2 Bimodal Recognition of Cognitive Load Based on Speech and Physiological Changes
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    Chapter 3 Human Mobility-Pattern Discovery and Next-Place Prediction from GPS Data
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    Chapter 4 Fusion Architectures for Multimodal Cognitive Load Recognition
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    Chapter 5 Face Recognition in Home Security System Using Tensor Decomposition Based on Radix-(2 × 2) Hierarchical SVD
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    Chapter 6 Performance Analysis of Gesture Recognition Classifiers for Building a Human Robot Interface
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    Chapter 7 On Automatic Question Answering Using Efficient Primal-Dual Models
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    Chapter 8 Hierarchical Bayesian Multiple Kernel Learning Based Feature Fusion for Action Recognition
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    Chapter 9 Audio Visual Speech Recognition Using Deep Recurrent Neural Networks
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    Chapter 10 Audio-Visual Recognition of Pain Intensity
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    Chapter 11 The SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain- and Emotion-Recognition System
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    Chapter 12 Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models
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    Chapter 13 Recursively Measured Action Units
Attention for Chapter 9: Audio Visual Speech Recognition Using Deep Recurrent Neural Networks
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Citations

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Readers on

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37 Mendeley
Summary Patents Dimensions citations
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Chapter title
Audio Visual Speech Recognition Using Deep Recurrent Neural Networks
Chapter number 9
Book title
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction
Published by
Springer, Cham, December 2016
DOI 10.1007/978-3-319-59259-6_9
Book ISBNs
978-3-31-959258-9, 978-3-31-959259-6
Authors

Abhinav Thanda, Shankar M. Venkatesan, Thanda, Abhinav, Venkatesan, Shankar M.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 30%
Student > Master 5 14%
Researcher 4 11%
Student > Bachelor 3 8%
Other 3 8%
Other 8 22%
Unknown 3 8%
Readers by discipline Count As %
Computer Science 19 51%
Engineering 11 30%
Social Sciences 2 5%
Agricultural and Biological Sciences 1 3%
Unknown 4 11%

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