Machine Learning Systems for Multimodal Affect Recognition by Markus Kächele.

Machine Learning Systems for Multimodal Affect Recognition

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...

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Bibliographic Details
Main Author: Kächele, Markus (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg, 2020.
Edition:1st ed. 2020.
Subjects:
Machine learning.
User interfaces (Computer systems)
Optical data processing.
Online Access: Full text (Wentworth users only)
Table of Contents:
  • Classification and Regression Approaches
  • Applications and Affective Corpora
  • Modalities and Feature Extraction
  • Machine Learning for the Estimation of Affective Dimensions
  • Adaptation and Personalization of Classifiers
  • Experimental Validation.

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