Quantifying and Processing Biomedical and Behavioral Signals
Buch in deiner Nähe kaufen
Beschreibung
The book is based on interdisciplinary research on various aspects and dynamics of human multimodal signal exchanges. It discusses realistic application scenarios where human interaction is the focus, in order to
- identify new methods for data processing and data flow coordination through synchronization, and optimization of new encoding features combining contextually enacted communicative signals, and
- develop shared digital data repositories and annotation standards for benchmarking the algorithmic feasibility and successive implementation of believable human–computer interaction (HCI) systems.
This book is a valuable resource for
a. the research community, PhD students, early stage researchers
c. schools, hospitals, and rehabilitation and assisted-living centers
e. the ICT market, and representatives from multimedia industries
The book is based on interdisciplinary research on various aspects and dynamics of human multimodal signal exchanges. It discusses realistic application scenarios where human interaction is the focus, in order to
- identify new methods for data processing and data flow coordination through synchronization, and optimization of new encoding features combining contextually enacted communicative signals, and
- develop shared digital data repositories and annotation standards for benchmarking the algorithmic feasibility and successive implementation of believable human–computer interaction (HCI) systems.
This book is a valuable resource for
a. the research community, PhD students, early stage researchers
c. schools, hospitals, and rehabilitation and assisted-living centers
e. the ICT market, and representatives from multimedia industries
Covers various scientific areas in machine learning, artificial neural networks, social and biometric data for applications in human–computer interactions Presents recent research in dynamic signal exchanges and demonstrates how these advances can characterize a more friendly human–machine interaction Proposes approaches to measure and quantify human behavior for the implementation of autonomous, and complex human–computer Interfaces Considers key aspects of the integration of algorithms and procedures for the recognition of dynamic (faces, speech, gaits, EEGs, brain and speech waves) signals, in anticipation of the implementation of useful applications such as intelligent avatars, interactive dialog systems, and reliable complex autonomous systems for human signal’s detection and identification Includes contributions from leading authorities in their respective fields
Autor*in
Anna Esposito
Themen in »Quantifying and Processing Biomedical and Behavioral Signals«
Machine Learning Methods User Modelling Neural Networks Artificial Intelligence Customer Care Situated Human-Computer Interaction (HCI) Social Science Scholarship Daily Life Activities Biometric Data Health & Well Being Social Signal Processing Social Behaviour and Context Complex Human-Computer Interfaces