Multi Modal Signal Processing
Download Multi Modal Signal Processing full books in PDF, epub, and Kindle. Read online free Multi Modal Signal Processing ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Jean-Philippe Thiran |
| Publisher | : Academic Press |
| Total Pages | : 343 |
| Release | : 2009-11-11 |
| Genre | : Computers |
| ISBN | : 0080888690 |
Multimodal signal processing is an important research and development field that processes signals and combines information from a variety of modalities – speech, vision, language, text – which significantly enhance the understanding, modelling, and performance of human-computer interaction devices or systems enhancing human-human communication. The overarching theme of this book is the application of signal processing and statistical machine learning techniques to problems arising in this multi-disciplinary field. It describes the capabilities and limitations of current technologies, and discusses the technical challenges that must be overcome to develop efficient and user-friendly multimodal interactive systems. With contributions from the leading experts in the field, the present book should serve as a reference in multimodal signal processing for signal processing researchers, graduate students, R&D engineers, and computer engineers who are interested in this emerging field. - Presents state-of-art methods for multimodal signal processing, analysis, and modeling - Contains numerous examples of systems with different modalities combined - Describes advanced applications in multimodal Human-Computer Interaction (HCI) as well as in computer-based analysis and modelling of multimodal human-human communication scenes.
| Author | : Steve Renals |
| Publisher | : Cambridge University Press |
| Total Pages | : 287 |
| Release | : 2012-06-07 |
| Genre | : Computers |
| ISBN | : 1107022290 |
A comprehensive synthesis of recent advances in multimodal signal processing applications for human interaction analysis and meeting support technology. With directly applicable methods and metrics along with benchmark results, this guide is ideal for those interested in multimodal signal processing, its component disciplines and its application to human interaction analysis.
| Author | : Sharon Oviatt |
| Publisher | : Morgan & Claypool |
| Total Pages | : 598 |
| Release | : 2017-06-01 |
| Genre | : Computers |
| ISBN | : 1970001666 |
The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces— user input involving new media (speech, multi-touch, gestures, writing) embedded in multimodal-multisensor interfaces. These interfaces support smart phones, wearables, in-vehicle and robotic applications, and many other areas that are now highly competitive commercially. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This first volume of the handbook presents relevant theory and neuroscience foundations for guiding the development of high-performance systems. Additional chapters discuss approaches to user modeling and interface designs that support user choice, that synergistically combine modalities with sensors, and that blend multimodal input and output. This volume also highlights an in-depth look at the most common multimodal-multisensor combinations—for example, touch and pen input, haptic and non-speech audio output, and speech-centric systems that co-process either gestures, pen input, gaze, or visible lip movements. A common theme throughout these chapters is supporting mobility and individual differences among users. These handbook chapters provide walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces should be designed in the future to most effectively advance human performance.
| Author | : Soham Sarkar |
| Publisher | : John Wiley & Sons |
| Total Pages | : 288 |
| Release | : 2021-04-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1119571421 |
A comprehensive review of the most recent applications of intelligent multi-modal data processing Intelligent Multi-Modal Data Processing contains a review of the most recent applications of data processing. The Editors and contributors – noted experts on the topic – offer a review of the new and challenging areas of multimedia data processing as well as state-of-the-art algorithms to solve the problems in an intelligent manner. The text provides a clear understanding of the real-life implementation of different statistical theories and explains how to implement various statistical theories. Intelligent Multi-Modal Data Processing is an authoritative guide for developing innovative research ideas for interdisciplinary research practices. Designed as a practical resource, the book contains tables to compare statistical analysis results of a novel technique to that of the state-of-the-art techniques and illustrations in the form of algorithms to establish a pre-processing and/or post-processing technique for model building. The book also contains images that show the efficiency of the algorithm on standard data set. This important book: Includes an in-depth analysis of the state-of-the-art applications of signal and data processing Contains contributions from noted experts in the field Offers information on hybrid differential evolution for optimal multilevel image thresholding Presents a fuzzy decision based multi-objective evolutionary method for video summarisation Written for students of technology and management, computer scientists and professionals in information technology, Intelligent Multi-Modal Data Processing brings together in one volume the range of multi-modal data processing.
| Author | : Xavier Alameda-Pineda |
| Publisher | : Academic Press |
| Total Pages | : 500 |
| Release | : 2018-11-13 |
| Genre | : Technology & Engineering |
| ISBN | : 0128146028 |
Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. - Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios - Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources - Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data
| Author | : Li Deng |
| Publisher | : |
| Total Pages | : 212 |
| Release | : 2014 |
| Genre | : Machine learning |
| ISBN | : 9781601988140 |
Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks
| Author | : Manuel F. Casanova |
| Publisher | : CRC Press |
| Total Pages | : 977 |
| Release | : 2017-01-06 |
| Genre | : Medical |
| ISBN | : 1315354195 |
This book covers state-of-the-art medical image analysis approaches currently pursued in autism research. Chapters cover recent advances in diagnosis using structural neuroimaging. All aspects of imaging are included, such as electrophysiology (EEG, ERP, QEEG, and MEG), postmortem techniques, and advantages and difficulties of depositing/acquiring images in larger databases. The book incorporates 2D, 3D, and 4D imaging and advances scientific research within the broad field of autism imaging.
| Author | : Abdulhamit Subasi |
| Publisher | : Elsevier |
| Total Pages | : 426 |
| Release | : 2024-09-18 |
| Genre | : Science |
| ISBN | : 0443291519 |
Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction presents an overview of an emerging field that is concerned with exploiting multiple modalities of communication in both Artificial Intelligence and Human-Machine Interaction. The book not only provides cross disciplinary research in the fields of multimodal signal acquisition and sensing, analysis, IoTs (Internet of Things), Artificial Intelligence, and system architectures, it also evaluates the role of Artificial Intelligence I in relation to the realization of contemporary Human Machine Interaction (HMI) systems.Readers are introduced to the multimodal signals and their role in the identification of the intended subjects, mental state and the realization of HMI systems are explored, and the applications of signal processing and machine/ensemble/deep learning for HMIs are assessed. A description of proposed methodologies is provided, and related works are also presented. This is a valuable resource for researchers, health professionals, postgraduate students, post doc researchers and faculty members in the fields of HMIs, Brain-Computer Interface (BCI), Prosthesis, Computer vision, and Mental state estimation, and all those who wish to broaden their knowledge in the allied field. - Covers advances in the multimodal signal processing and artificial intelligence assistive HMIs - Presents theories, algorithms, realizations, applications, approaches, and challenges that will have their impact and contribution in the design and development of modern and effective HMI (Human Machine Interaction) system - Presents different aspects of the multimodal signals, from the sensing to analysis using hardware/software, and making use of machine/ensemble/deep learning in the intended problem-solving
| Author | : Ervin Sejdic |
| Publisher | : CRC Press |
| Total Pages | : 1235 |
| Release | : 2018-07-04 |
| Genre | : Medical |
| ISBN | : 1351061216 |
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.
| Author | : Hua Xu |
| Publisher | : Springer Nature |
| Total Pages | : 278 |
| Release | : 2023-11-26 |
| Genre | : Technology & Engineering |
| ISBN | : 9819957761 |
The natural interaction ability between human and machine mainly involves human-machine dialogue ability, multi-modal sentiment analysis ability, human-machine cooperation ability, and so on. To enable intelligent computers to have multi-modal sentiment analysis ability, it is necessary to equip them with a strong multi-modal sentiment analysis ability during the process of human-computer interaction. This is one of the key technologies for efficient and intelligent human-computer interaction. This book focuses on the research and practical applications of multi-modal sentiment analysis for human-computer natural interaction, particularly in the areas of multi-modal information feature representation, feature fusion, and sentiment classification. Multi-modal sentiment analysis for natural interaction is a comprehensive research field that involves the integration of natural language processing, computer vision, machine learning, pattern recognition, algorithm, robot intelligent system, human-computer interaction, etc. Currently, research on multi-modal sentiment analysis in natural interaction is developing rapidly. This book can be used as a professional textbook in the fields of natural interaction, intelligent question answering (customer service), natural language processing, human-computer interaction, etc. It can also serve as an important reference book for the development of systems and products in intelligent robots, natural language processing, human-computer interaction, and related fields.
