Deep Learning Techniques Applied To Affective Computing
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Deep Learning Techniques Applied To Affective Computing
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Author : Zhen Cui
language : en
Publisher: Frontiers Media SA
Release Date : 2023-06-14
Deep Learning Techniques Applied To Affective Computing written by Zhen Cui and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-14 with Science categories.
Affective computing refers to computing that relates to, arises from, or influences emotions. The goal of affective computing is to bridge the gap between humans and machines and ultimately endow machines with emotional intelligence for improving natural human-machine interaction. In the context of human-robot interaction (HRI), it is hoped that robots can be endowed with human-like capabilities of observation, interpretation, and emotional expression. The research on affective computing has recently achieved extensive progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing concentrates on estimating human emotions through different forms of signals such as speech, face, text, EEG, fMRI, and many others. In neuroscience, the neural mechanisms of emotion are explored by combining neuroscience with the psychological study of personality, emotion, and mood. In psychology and philosophy, emotion typically includes a subjective, conscious experience characterized primarily by psychophysiological expressions, biological reactions, and mental states. The multi-disciplinary features of understanding “emotion” result in the fact that inferring the emotion of humans is definitely difficult. As a result, a multi-disciplinary approach is required to facilitate the development of affective computing. One of the challenging problems in affective computing is the affective gap, i.e., the inconsistency between the extracted feature representations and subjective emotions. To bridge the affective gap, various hand-crafted features have been widely employed to characterize subjective emotions. However, these hand-crafted features are usually low-level, and they may hence not be discriminative enough to depict subjective emotions. To address this issue, the recently-emerged deep learning (also called deep neural networks) techniques provide a possible solution. Due to the used multi-layer network structure, deep learning techniques are capable of learning high-level contributing features from a large dataset and have exhibited excellent performance in multiple application domains such as computer vision, signal processing, natural language processing, human-computer interaction, and so on. The goal of this Research Topic is to gather novel contributions on deep learning techniques applied to affective computing across the diverse fields of psychology, machine learning, neuroscience, education, behavior, sociology, and computer science to converge with those active in other research areas, such as speech emotion recognition, facial expression recognition, Electroencephalogram (EEG) based emotion estimation, human physiological signal (heart rate) estimation, affective human-robot interaction, multimodal affective computing, etc. We welcome researchers to contribute their original papers as well as review articles to provide works regarding the neural approach from computation to affective computing systems. This Research Topic aims to bring together research including, but not limited to: • Deep learning architectures and algorithms for affective computing tasks such as emotion recognition from speech, face, text, EEG, fMRI, and many others. • Explainability of deep Learning algorithms for affective computing. • Multi-task learning techniques for emotion, personality and depression detection, etc. • Novel datasets for affective computing • Applications of affective computing in robots, such as emotion-aware human-robot interaction and social robots, etc.
Applied Affective Computing
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Author : Leimin Tian
language : en
Publisher: Morgan & Claypool
Release Date : 2022-02-04
Applied Affective Computing written by Leimin Tian and has been published by Morgan & Claypool this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-04 with Computers categories.
Affective computing is a nascent field situated at the intersection of artificial intelligence with social and behavioral science. It studies how human emotions are perceived and expressed, which then informs the design of intelligent agents and systems that can either mimic this behavior to improve their intelligence or incorporate such knowledge to effectively understand and communicate with their human collaborators. Affective computing research has recently seen significant advances and is making a critical transformation from exploratory studies to real-world applications in the emerging research area known as applied affective computing. This book offers readers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. It provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being. It also addresses ethical concerns related to affective computing and how to prevent misuse of the technology in research and applications. Further, this book identifies future directions for the field and summarizes a set of guidelines for developing next-generation affective computing systems that are effective, safe, and human-centered. For researchers and practitioners new to affective computing, this book will serve as an introduction to the field to help them in identifying new research topics or developing novel applications. For more experienced researchers and practitioners, the discussions in this book provide guidance for adopting a human-centered design and development approach to advance affective computing.
The Oxford Handbook Of Affective Computing
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Author : Rafael A. Calvo
language : en
Publisher:
Release Date : 2015
The Oxford Handbook Of Affective Computing written by Rafael A. Calvo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.
The Oxford Handbook of Affective Computing is the definitive reference for research in Affective Computing (AC), a growing multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and many other disciplines. The handbook explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems that intricately involve affect at their core. Suitable for use as a textbook in undergraduate or graduate courses in AC, the volume is a valuable resource for students, researchers, and practitioners worldwide.
Smart Computer Vision
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Author : B. Vinoth Kumar
language : en
Publisher: Springer Nature
Release Date : 2023-02-27
Smart Computer Vision written by B. Vinoth Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-27 with Technology & Engineering categories.
This book addresses and disseminates research and development in the applications of intelligent techniques for computer vision, the field that works on enabling computers to see, identify, and process images in the same way that human vision does, and then providing appropriate output. The book provides contributions which include theory, case studies, and intelligent techniques pertaining to computer vision applications. The book helps readers grasp the essence of the recent advances in this complex field. The audience includes researchers, professionals, practitioners, and students from academia and industry who work in this interdisciplinary field. The authors aim to inspire future research both from theoretical and practical viewpoints to spur further advances in the field.
Recent Advances In Machine Learning Techniques And Sensor Applications For Human Emotion Activity Recognition And Support
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Author : Kyandoghere Kyamakya
language : en
Publisher: Springer Nature
Release Date : 2024-11-07
Recent Advances In Machine Learning Techniques And Sensor Applications For Human Emotion Activity Recognition And Support written by Kyandoghere Kyamakya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-07 with Computers categories.
This book explores integrating machine learning techniques and sensor applications for human emotion and activity recognition, creating personalized and effective support systems. It covers state-of-the-art machine learning techniques and large language models using multimodal sensors. Enhancing the quality of life for individuals with special needs, particularly the elderly, is a key focus in Active and Assisted Living (AAL) research. Unlike other literature, it emphasizes support mechanisms along with recognition, using metamodel integration for adaptable AAL systems. This book offers insights into technologies transforming AAL for researchers, students, and practitioners. It is a valuable resource for developing responsive and personalized support systems that enhance life quality in smart environments. It is also essential for advancing the understanding of machine learning and sensor technologies in AAL and emotion recognition.
Bridging The Gap Between Machine Learning And Affective Computing
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Author : Zhen Cui
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-05
Bridging The Gap Between Machine Learning And Affective Computing written by Zhen Cui and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-05 with Science categories.
Affective computing refers to computing that relates to, arises from, or influences emotions, as pioneered by Rosalind Picard in 1995. The goal of affective computing is to bridge the gap between human and machines and ultimately enable robots to communicate with human naturally and emotionally. Recently, the research on affective computing has gained considerable progress with many fields contributing including neuroscience, psychology, education, medicine, behavior, sociology, and computer science. Current research in affective computing mainly focuses on estimating of human emotions through different forms of signals, e.g., face video, EEG, Speech, PET scans or fMRI. Inferring the emotion of humans is difficult, as emotion is a subjective, unconscious experience characterized primarily by psycho-physiological expressions and biological reactions. It is influenced by hormones and neurotransmitters such as dopamine, noradrenaline, serotonin, oxytocin, GABA… etc. The physiology of emotion is closely linked to arousal of the nervous system with various states and strengths relating, apparently, to different particular emotions. To understand “emotion” or “affect” merely by machine learning or big data analysis is not enough, but the understanding and applications from the intrinsic features of emotions from the neuroscience aspect is essential.
Machine And Deep Learning Techniques For Emotion Detection
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Author : Rai, Mritunjay
language : en
Publisher: IGI Global
Release Date : 2024-05-14
Machine And Deep Learning Techniques For Emotion Detection written by Rai, Mritunjay and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-14 with Psychology categories.
Computer understanding of human emotions has become crucial and complex within the era of digital interaction and artificial intelligence. Emotion detection, a field within AI, holds promise for enhancing user experiences, personalizing services, and revolutionizing industries. However, navigating this landscape requires a deep understanding of machine and deep learning techniques and the interdisciplinary challenges accompanying them. Machine and Deep Learning Techniques for Emotion Detection offer a comprehensive solution to this pressing problem. Designed for academic scholars, practitioners, and students, it is a guiding light through the intricate terrain of emotion detection. By blending theoretical insights with practical implementations and real-world case studies, our book equips readers with the knowledge and tools needed to advance the frontier of emotion analysis using machine and deep learning methodologies.
Advanced Applications Of Generative Ai And Natural Language Processing Models
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Author : Obaid, Ahmed J.
language : en
Publisher: IGI Global
Release Date : 2023-12-21
Advanced Applications Of Generative Ai And Natural Language Processing Models written by Obaid, Ahmed J. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-21 with Computers categories.
The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.
Affective Computing And Intelligent Interaction
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Author : Sidney D ́Mello
language : en
Publisher: Springer
Release Date : 2011-10-18
Affective Computing And Intelligent Interaction written by Sidney D ́Mello and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-18 with Computers categories.
The two-volume set LNCS 6974 and LNCS 6975 constitutes the refereed proceedings of the Fourth International Conference on Affective Computing and Intelligent Interaction, ACII 2011, held in Memphis,TN, USA, in October 2011. The 135 papers in this two volume set presented together with 3 invited talks were carefully reviewed and selected from 196 submissions. The papers are organized in topical sections on recognition and synthesis of human affect, affect-sensitive applications, methodological issues in affective computing, affective and social robotics, affective and behavioral interfaces, relevant insights from psychology, affective databases, Evaluation and annotation tools.
Biomedical Applications Based On Natural And Artificial Computing
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Author : José Manuel Ferrández Vicente
language : en
Publisher: Springer
Release Date : 2017-06-10
Biomedical Applications Based On Natural And Artificial Computing written by José Manuel Ferrández Vicente and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-10 with Computers categories.
The two volumes LNCS 10337 and 10338 constitute the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2017, held in Corunna, Spain, in June 2017. The total of 102 full papers was carefully reviewed and selected from 194 submissions during two rounds of reviewing and improvement. The papers are organized in two volumes, one on natural and artificial computation for biomedicine and neuroscience, addressing topics such as theoretical neural computation; models; natural computing in bioinformatics; physiological computing in affective smart environments; emotions; as well as signal processing and machine learning applied to biomedical and neuroscience applications. The second volume deals with biomedical applications, based on natural and artificial computing and addresses topics such as biomedical applications; mobile brain computer interaction; human robot interaction; deep learning; machine learning applied to big data analysis; computational intelligence in data coding and transmission; and applications.