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Author : Blaž Škrlj
Publisher : Springer Nature
ISBN 13 : 3031570162
Total Pages : 78 pages
Book Rating : 4.62/5 ( download)
Download or read book From Unimodal to Multimodal Machine Learning written by Blaž Škrlj and published by Springer Nature. This book was released on with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Santosh Kumar
Publisher : Academic Press
ISBN 13 : 9780128237373
Total Pages : 375 pages
Book Rating : 4.76/5 ( download)
Download or read book Multimodal Machine Learning written by Santosh Kumar and published by Academic Press. This book was released on 2021-05-15 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimodal Machine Learning: Techniques and Applications explains recent advances in multimodal machine learning, providing a coherent set of fundamentals for designing efficient multimodal learning algorithms for different applications. The book addresses the main challenges in multimodal machine learning based computing paradigms, including multimodal representation learning, translation and mapping, modality alignment, multimodal fusion and co-learning. The book also explores the important texture feature descriptors based on recognition and transform techniques. It is ideal for senior undergraduates, graduate students, and researchers in data science, engineering, computer science and statistics. Presents new representation, classification and identification algorithms for data prediction and analysis on feature characteristics Discusses recent and future advancements in diversified fields of computer vision , pattern recognition, generative adversarial network-based learning, video analytics and data science Provides an overview of future research challenges and directions
Author : Hua Xu
Publisher : Springer Nature
ISBN 13 : 9819957761
Total Pages : 278 pages
Book Rating : 4.67/5 ( download)
Download or read book Multi-Modal Sentiment Analysis written by Hua Xu and published by Springer Nature. This book was released on 2023-11-26 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Soujanya Poria
Publisher : Springer
ISBN 13 : 3319950207
Total Pages : 214 pages
Book Rating : 4.04/5 ( download)
Download or read book Multimodal Sentiment Analysis written by Soujanya Poria and published by Springer. This book was released on 2018-10-24 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.
Author : Steve Renals
Publisher : Springer
ISBN 13 : 3540692681
Total Pages : 482 pages
Book Rating : 4.83/5 ( download)
Download or read book Machine Learning for Multimodal Interaction written by Steve Renals and published by Springer. This book was released on 2007-01-23 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Machine Learning for Multimodal Interaction, MLMI 2006, held in Bethesda, MD, USA, in May 2006. The papers are organized in topical sections on multimodal processing, image and video processing, HCI and applications, discourse and dialogue, speech and audio processing, and NIST meeting recognition evaluation.
Author : Sandeep Kumar
Publisher : John Wiley & Sons
ISBN 13 : 1119785472
Total Pages : 340 pages
Book Rating : 4.77/5 ( download)
Download or read book Multimodal Biometric and Machine Learning Technologies written by Sandeep Kumar and published by John Wiley & Sons. This book was released on 2023-10-18 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: MULTIMODAL BIOMETRIC AND MACHINE LEARNING TECHNOLOGIES With an increasing demand for biometric systems in various industries, this book on multimodal biometric systems, answers the call for increased resources to help researchers, developers, and practitioners. Multimodal biometric and machine learning technologies have revolutionized the field of security and authentication. These technologies utilize multiple sources of information, such as facial recognition, voice recognition, and fingerprint scanning, to verify an individual???s identity. The need for enhanced security and authentication has become increasingly important, and with the rise of digital technologies, cyber-attacks and identity theft have increased exponentially. Traditional authentication methods, such as passwords and PINs, have become less secure as hackers devise new ways to bypass them. In this context, multimodal biometric and machine learning technologies offer a more secure and reliable approach to authentication. This book provides relevant information on multimodal biometric and machine learning technologies and focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity. The book provides content on the theory of multimodal biometric design, evaluation, and user diversity, and explains the underlying causes of the social and organizational problems that are typically devoted to descriptions of rehabilitation methods for specific processes. Furthermore, the book describes new algorithms for modeling accessible to scientists of all varieties. Audience Researchers in computer science and biometrics, developers who are designing and implementing biometric systems, and practitioners who are using biometric systems in their work, such as law enforcement personnel or healthcare professionals.
Author : M. Arif Wani
Publisher : Springer Nature
ISBN 13 : 9811961530
Total Pages : 394 pages
Book Rating : 4.33/5 ( download)
Download or read book Deep Learning Applications, Volume 4 written by M. Arif Wani and published by Springer Nature. This book was released on 2022-11-25 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. The book is fourth in the series published since 2017.
Author : Sharon Oviatt
Publisher : Morgan & Claypool
ISBN 13 : 1970001690
Total Pages : 555 pages
Book Rating : 4.93/5 ( download)
Download or read book The Handbook of Multimodal-Multisensor Interfaces, Volume 2 written by Sharon Oviatt and published by Morgan & Claypool. This book was released on 2018-10-08 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. 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 second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides 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 rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.
Author : Richard Golden
Publisher : CRC Press
ISBN 13 : 1351051490
Total Pages : 525 pages
Book Rating : 4.91/5 ( download)
Download or read book Statistical Machine Learning written by Richard Golden and published by CRC Press. This book was released on 2020-06-24 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent rapid growth in the variety and complexity of new machine learning architectures requires the development of improved methods for designing, analyzing, evaluating, and communicating machine learning technologies. Statistical Machine Learning: A Unified Framework provides students, engineers, and scientists with tools from mathematical statistics and nonlinear optimization theory to become experts in the field of machine learning. In particular, the material in this text directly supports the mathematical analysis and design of old, new, and not-yet-invented nonlinear high-dimensional machine learning algorithms. Features: Unified empirical risk minimization framework supports rigorous mathematical analyses of widely used supervised, unsupervised, and reinforcement machine learning algorithms Matrix calculus methods for supporting machine learning analysis and design applications Explicit conditions for ensuring convergence of adaptive, batch, minibatch, MCEM, and MCMC learning algorithms that minimize both unimodal and multimodal objective functions Explicit conditions for characterizing asymptotic properties of M-estimators and model selection criteria such as AIC and BIC in the presence of possible model misspecification This advanced text is suitable for graduate students or highly motivated undergraduate students in statistics, computer science, electrical engineering, and applied mathematics. The text is self-contained and only assumes knowledge of lower-division linear algebra and upper-division probability theory. Students, professional engineers, and multidisciplinary scientists possessing these minimal prerequisites will find this text challenging yet accessible. About the Author: Richard M. Golden (Ph.D., M.S.E.E., B.S.E.E.) is Professor of Cognitive Science and Participating Faculty Member in Electrical Engineering at the University of Texas at Dallas. Dr. Golden has published articles and given talks at scientific conferences on a wide range of topics in the fields of both statistics and machine learning over the past three decades. His long-term research interests include identifying conditions for the convergence of deterministic and stochastic machine learning algorithms and investigating estimation and inference in the presence of possibly misspecified probability models.
Author : Hamid R. Rabiee
Publisher : Frontiers Media SA
ISBN 13 : 2832510299
Total Pages : 361 pages
Book Rating : 4.92/5 ( download)
Download or read book Machine learning in neuroscience written by Hamid R. Rabiee and published by Frontiers Media SA. This book was released on 2023-01-27 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt:
