Multimodal Affective Computing: Technologies and Applications in Learning Environments

Cabada, Ramón Zatarain, López, Héctor Manuel Cárdenas, Escalante, Hugo Jair

Multimodal Affective Computing: Technologies and Applications in Learning Environments
  • 出版商: Springer
  • 出版日期: 2024-06-28
  • 售價: $7,030
  • 貴賓價: 9.5 折 $6,679
  • 語言: 英文
  • 頁數: 213
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3031325443
  • ISBN-13: 9783031325441

    • 海外代購書籍(需單獨結帳)

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商品描述

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 learningsystem. 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.

This book can be very useful not only for beginners who are interested in affective computing and intelligent learning environments, but also for advanced and experts in the practice and developments of the field. It complies an end-to-end treatment on these subjects, especially with educational applications, making it easy for researchers and students to get on track with fundamentals, established methodologies, conventional evaluation protocols, and the latest progress on these subjects.

作者簡介

Ramon Zatarain Cabada. Professor and Researcher at the Instituto Tecnológico de Culiacán, Mexico. He is a regular member of the Mexican Academy of Computing (AMEXCOMP), the Mexican Society of Artificial Intelligence (SMIA), and the Mexican System of Researchers Level I (SNI). He has been a professor and Researcher at institutions such as Instituto Tecnológico de Toluca, the University of the State of México (UAEM), and the Instituto Tecnológico de Aguascalientes. He was a leader to create programs for Computer Science (Master and PhD). He has served as co-editor of a special issue of Educational Technology and Society and author of chapters in different Springer books such as Soft Computing for Recognition Based on Biometrics, Social Networking and Education, and Current Trends on Knowledge-Based Systems. As a researcher he has been a leader in more than 20 research projects and has more than 100 publications in different international journals and proceedings. His researchinterests are on Intelligent Learning Environments, Affective Computing, and Artificial Intelligence applied to Education.
Héctor Manuel Cárdenas López. Research assistant at the Instituto Tecnológico de Culiacán, Mexico. He is currently working towards a PhD degree in Engineering Sciences with the topic Multimodal Emotion and Personality Recognition. He is a member of the Thematic Network of Applied Computational Intelligence (RedICA). His main research interest includes Multimodal deep learning techniques, human behavior classification for emotion and personality recognition, affective tutoring systems, and cognitive oriented emotions.
Hugo Jair Escalante. Senior researcher scientist INAOE, Mexico and member of the board of directors of ChaLearn USA, Chair officer of the IAPR Technical Committee 12. He is a regular member of the Mexican Academy of Sciences (AMC), the Mexican Academy of Computing (AMEXCOMP) and Mexican System of Researchers Level II (SNI). He was editor of the Springer Series on Challenges in Machine Learning 2017-2023 and is Associate Editor of IEEE Transactions on Affective Computing. He has been involved in the organization of several challenges in machine learning and computer vision collocated with top venues. He has served as competition chair of NeurIPS2020, FG2020 and ICPR2020, NeurIPS2019, PAKDD2019-2018, IJCNN2019. His research interests are on machine learning, challenge organization, and its applications on language and vision.

作者簡介(中文翻譯)

**Ramon Zatarain Cabada**。墨西哥庫利亞坎科技學院的教授及研究員。他是墨西哥計算機學院（AMEXCOMP）、墨西哥人工智慧學會（SMIA）及墨西哥研究人員系統I級（SNI）的正式成員。他曾在托盧卡科技學院、墨西哥州立大學（UAEM）及阿瓜斯卡連特斯科技學院擔任教授及研究員。他是計算機科學（碩士及博士）課程的創建領導者。他曾擔任《教育科技與社會》特刊的共同編輯，並在不同的Springer書籍中撰寫章節，如《基於生物識別的軟計算》、《社交網絡與教育》及《基於知識的系統的當前趨勢》。作為研究員，他領導了超過20個研究項目，並在不同的國際期刊和會議上發表了超過100篇論文。他的研究興趣包括智能學習環境、情感計算及應用於教育的人工智慧。

**Héctor Manuel Cárdenas López**。墨西哥庫利亞坎科技學院的研究助理。他目前正在攻讀工程科學的博士學位，研究主題為多模態情感與人格識別。他是應用計算智能主題網絡（RedICA）的成員。他的主要研究興趣包括多模態深度學習技術、人類行為分類以進行情感與人格識別、情感輔導系統及認知導向情感。

**Hugo Jair Escalante**。墨西哥INAOE的高級研究科學家及ChaLearn USA董事會成員，IAPR技術委員會12的主席。他是墨西哥科學院（AMC）、墨西哥計算機學院（AMEXCOMP）及墨西哥研究人員系統II級（SNI）的正式成員。他曾擔任Springer機器學習挑戰系列的編輯（2017-2023），並是IEEE情感計算期刊的副編輯。他參與了多個與頂尖會議共同舉辦的機器學習和計算機視覺挑戰的組織工作。他曾擔任NeurIPS2020、FG2020及ICPR2020的競賽主席，以及NeurIPS2019、PAKDD2019-2018及IJCNN2019的競賽主席。他的研究興趣包括機器學習、挑戰組織及其在語言和視覺上的應用。

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