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Machine Learning Systems for Multimodal Affect Recognition

Authors: Kächele, Markus

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  • A Study in Neuroinformatics

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About this book

Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlighted. Furthermore, methods are presented that allow personalization of datasets and adaptation of classifiers to new situations and persons. 

About the authors

Dr. Markus Kächele is managing partner of Ikara Vision Systems, a spin-off of the German Research Center for Artificial Intelligence (DFKI). He focuses on bridging the gap between research and industrial applications in the fields of deep learning and computer vision.

Table of contents (10 chapters)

Table of contents (10 chapters)

Buy this book

eBook $59.99
price for USA (gross)
  • ISBN 978-3-658-28674-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $74.99
price for USA
  • ISBN 978-3-658-28673-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning Systems for Multimodal Affect Recognition
Authors
Copyright
2020
Publisher
Springer Vieweg
Copyright Holder
Springer Fachmedien Wiesbaden GmbH, part of Springer Nature
eBook ISBN
978-3-658-28674-3
DOI
10.1007/978-3-658-28674-3
Softcover ISBN
978-3-658-28673-6
Edition Number
1
Number of Pages
XIX, 188
Number of Illustrations
1 b/w illustrations
Topics