Machine Learning Systems for Multimodal Affect Recognition

Released on by Markus Kächele
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  • Machine Learning Systems for Multimodal Affect Recognition Book Detail

  • Author : Markus Kächele
  • Release Date : 2019-11-19
  • Publisher : Springer Nature
  • Genre : Computers
  • Pages : 188
  • ISBN 13 : 3658286741
  • File Size : 87,87 MB
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Machine Learning Systems for Multimodal Affect Recognition by Markus Kächele PDF Summary

Book Description: 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.

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Multimodal Affective Computing

Multimodal Affective Computing

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This book explores AI methodologies for the implementation of affective states in intelligent learning environments. Divided into four parts, Multimodal Affecti