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Machine Learning Systems for Multimodal Affect Recognition - Markus Kächele

Machine Learning Systems for Multimodal Affect Recognition

(Autor)

Buch | Softcover
XIX, 188 Seiten
2019 | 1st ed. 2020
Springer Fachmedien Wiesbaden GmbH (Verlag)
978-3-658-28673-6 (ISBN)
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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. 

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.

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.

Erscheinungsdatum
Zusatzinfo XIX, 188 p. 1 illus.
Verlagsort Wiesbaden
Sprache englisch
Maße 148 x 210 mm
Gewicht 278 g
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Software Entwicklung User Interfaces (HCI)
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Affective computing • Continuous Emotion Recognition • Human-Computer interaction • Human–Computer Interaction • machine learning • Multimodal Affect Recognition • Neural networks • Pain Intensity Estimation
ISBN-10 3-658-28673-3 / 3658286733
ISBN-13 978-3-658-28673-6 / 9783658286736
Zustand Neuware
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