Overview
- A Study in Neuroinformatics
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
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.
Authors and Affiliations
About the author
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.
Bibliographic Information
Book Title: Machine Learning Systems for Multimodal Affect Recognition
Authors: Markus Kächele
DOI: https://doi.org/10.1007/978-3-658-28674-3
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020
Softcover ISBN: 978-3-658-28673-6Published: 03 December 2019
eBook ISBN: 978-3-658-28674-3Published: 19 November 2019
Edition Number: 1
Number of Pages: XIX, 188
Number of Illustrations: 1 b/w illustrations
Topics: Machine Learning, User Interfaces and Human Computer Interaction, Computer Imaging, Vision, Pattern Recognition and Graphics