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Multimodal Affective Computing Technologies And Applications In Learning Environments Ramn Zatarain Cabada Hctor Manuel Crdenas Lpez Hugo Jair Escalante

  • SKU: BELL-50637416
Multimodal Affective Computing Technologies And Applications In Learning Environments Ramn Zatarain Cabada Hctor Manuel Crdenas Lpez Hugo Jair Escalante
$ 31.00 $ 45.00 (-31%)

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Multimodal Affective Computing Technologies And Applications In Learning Environments Ramn Zatarain Cabada Hctor Manuel Crdenas Lpez Hugo Jair Escalante instant download after payment.

Publisher: Springer International Publishing
File Extension: EPUB
File size: 17.42 MB
Pages: 211
Author: Ramón Zatarain Cabada; Héctor Manuel Cárdenas López; Hugo Jair Escalante
ISBN: 9783031325427, 3031325427
Language: English
Year: 2023

Product desciption

Multimodal Affective Computing Technologies And Applications In Learning Environments Ramn Zatarain Cabada Hctor Manuel Crdenas Lpez Hugo Jair Escalante by Ramón Zatarain Cabada; Héctor Manuel Cárdenas López; Hugo Jair Escalante 9783031325427, 3031325427 instant download after payment.

This book explores AI methodologies for the implementation of affective states in intelligent learning environments. Divided into four parts, Multimodal Affective Computing: Technologies and Applications in Learning Environments begins with an overview of Affective Computing and Intelligent Learning Environments, from their fundamentals and essential theoretical support up to their fusion and some successful practical applications. The basic concepts of Affective Computing, Machine Learning, and Pattern Recognition in Affective Computing, and Affective Learning Environments are presented in a comprehensive and easy-to-read manner. In the second part, a review on the emerging field of Sentiment Analysis for Learning Environments is introduced, including a systematic descriptive tour through topics such as building resources for sentiment detection, methods for data representation, designing and testing the classification models, and model integration into a learning system. The methodologies corresponding to Multimodal Recognition of Learning-Oriented Emotions are presented in the third part of the book, where topics such as building resources for emotion detection, methods for data representation, multimodal recognition systems, and multimodal emotion recognition in learning environments are presented. The fourth and last part of the book is devoted to a wide application field of the combination of methodologies, such as Automatic Personality Recognition, dealing with issues such as building resources for personality recognition, methods for data representation, personality recognition models, and multimodal personality recognition for affective computing.

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