Machine Learning Systems for Multimodal Affect Recognition
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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....
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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.

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ProduktnavnMachine Learning Systems for Multimodal Affect Recognition
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