From Unimodal To Multimodal Machine Learning
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From Unimodal To Multimodal Machine Learning
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Author : Blaž Škrlj
language : en
Publisher: Springer Nature
Release Date : 2024-05-21
From Unimodal To Multimodal Machine Learning written by Blaž Škrlj and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-21 with Mathematics categories.
With the increasing amount of various data types, machine learning methods capable of leveraging diverse sources of information have become highly relevant. Deep learning-based approaches have made significant progress in learning from texts and images in recent years. These methods enable simultaneous learning from different types of representations (embeddings). Substantial advancements have also been made in joint learning from different types of spaces. Additionally, other modalities such as sound, physical signals from the environment, and time series-based data have been recently explored. Multimodal machine learning, which involves processing and learning from data across multiple modalities, has opened up new possibilities in a wide range of applications, including speech recognition, natural language processing, and image recognition. From Unimodal to Multimodal Machine Learning: An Overview gradually introduces the concept of multimodal machine learning, providing readers with the necessary background to understand this type of learning and its implications. Key methods representative of different modalities are described in more detail, aiming to offer an understanding of the peculiarities of various types of data and how multimodal approaches tend to address them (although not yet in some cases). The book examines the implications of multimodal learning in other domains and presents alternative approaches that offer computationally simpler yet still applicable solutions. The final part of the book focuses on intriguing open research problems, making it useful for practitioners who wish to better understand the limitations of existing methods and explore potential research avenues to overcome them
Multimodal Biometric And Machine Learning Technologies
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Author : Sandeep Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2023-11-15
Multimodal Biometric And Machine Learning Technologies written by Sandeep Kumar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-15 with Computers categories.
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.
Deep Learning Applications Volume 4
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Author : M. Arif Wani
language : en
Publisher: Springer Nature
Release Date : 2022-11-25
Deep Learning Applications Volume 4 written by M. Arif Wani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-25 with Technology & Engineering categories.
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.
Deep Learning For Multimedia Processing Applications
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Author : Uzair Aslam Bhatti
language : en
Publisher: CRC Press
Release Date : 2024-02-21
Deep Learning For Multimedia Processing Applications written by Uzair Aslam Bhatti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing. Divided into two volumes, Volume Two delves into advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), explaining their unique capabilities in multimedia tasks. Readers will discover how deep learning techniques enable accurate and efficient image recognition, object detection, semantic segmentation, and image synthesis. The book also covers video analysis techniques, including action recognition, video captioning, and video generation, highlighting the role of deep learning in extracting meaningful information from videos. Furthermore, the book explores audio processing tasks such as speech recognition, music classification, and sound event detection using deep learning models. It demonstrates how deep learning algorithms can effectively process audio data, opening up new possibilities in multimedia applications. Lastly, the book explores the integration of deep learning with natural language processing techniques, enabling systems to understand, generate, and interpret textual information in multimedia contexts. Throughout the book, practical examples, code snippets, and real-world case studies are provided to help readers gain hands-on experience in implementing deep learning solutions for multimedia processing. Deep Learning for Multimedia Processing Applications is an essential resource for anyone interested in harnessing the power of deep learning to unlock the vast potential of multimedia data.
Empirical Approach To Machine Learning
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Author : Plamen P. Angelov
language : en
Publisher: Springer
Release Date : 2018-10-17
Empirical Approach To Machine Learning written by Plamen P. Angelov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-17 with Computers categories.
This book provides a ‘one-stop source’ for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today’s data-driven world. After an introduction to the fundamentals, the book discusses in depth anomaly detection, data partitioning and clustering, as well as classification and predictors. It describes classifiers of zero and first order, and the new, highly efficient and transparent deep rule-based classifiers, particularly highlighting their applications to image processing. Local optimality and stability conditions for the methods presented are formally derived and stated, while the software is also provided as supplemental, open-source material. The book will greatly benefit postgraduate students, researchers and practitioners dealing with advanced data processing, applied mathematicians, software developers of agent-oriented systems, and developers of embedded and real-time systems. Itcan also be used as a textbook for postgraduate coursework; for this purpose, a standalone set of lecture notes and corresponding lab session notes are available on the same website as the code. Dimitar Filev, Henry Ford Technical Fellow, Ford Motor Company, USA, and Member of the National Academy of Engineering, USA: “The book Empirical Approach to Machine Learning opens new horizons to automated and efficient data processing.” Paul J. Werbos, Inventor of the back-propagation method, USA: “I owe great thanks to Professor Plamen Angelov for making this important material available to the community just as I see great practical needs for it, in the new area of making real sense of high-speed data from the brain.” Chin-Teng Lin, Distinguished Professor at University of Technology Sydney, Australia: “This new book will set up a milestone for the modern intelligent systems.” Edward Tunstel, President of IEEE Systems, Man, Cybernetics Society, USA: “Empirical Approach to Machine Learning provides an insightful and visionary boost of progress in the evolution of computational learning capabilities yielding interpretable and transparent implementations.”
The Handbook Of Multimodal Multisensor Interfaces Volume 2
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Author : Sharon Oviatt
language : en
Publisher: Morgan & Claypool
Release Date : 2018-10-08
The Handbook Of Multimodal Multisensor Interfaces Volume 2 written by Sharon Oviatt and has been published by Morgan & Claypool this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-08 with Computers categories.
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.
Natural Language Processing And Chinese Computing
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Author : Wei Lu
language : en
Publisher: Springer Nature
Release Date : 2022-09-23
Natural Language Processing And Chinese Computing written by Wei Lu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-23 with Computers categories.
This two-volume set of LNAI 13551 and 13552 constitutes the refereed proceedings of the 11th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2022, held in Guilin, China, in September 2022. The 62 full papers, 21 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 327 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability.
Advances In Multimodal Learning Pedagogies Technologies And Analytics
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Author : Heng Luo
language : en
Publisher: Frontiers Media SA
Release Date : 2023-11-15
Advances In Multimodal Learning Pedagogies Technologies And Analytics written by Heng Luo 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 2023-11-15 with Science categories.
The 13th Conference On Information Technology And Its Applications
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2024-11-07
The 13th Conference On Information Technology And Its Applications written by Ngoc Thanh Nguyen 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 presents selected papers from the 13th International Conference on Information Technology and its Applications (CITA 2024) which took place on July 19–20, 2024. The 13th CITA will be hosted by the Vietnam-Korea University of Information and Communication Technology (VKU), a member of University of Danang, with the supports of the researching and training institutions belonging to ASEAN Consortium for Innovation and Research (ACIR) as well as Vietnam ICT Association of Faculties-Institutes-School-Universities (FISU Vietnam). The conference will take place in Da Nang City and Hoi An City which are beautiful and livable cities in Vietnam. All papers submitted to CITA 2024 are reviewed seriously, closely, and thoroughly by 02-04 reviewers with appropriate expertise, with professional advice from reputable scientists in the fields of information and communication technology. Over the past 13 years of establishment and development, CITA has become an international scientific conference with a prestigious brand in the scientific community not only in Vietnam but also around the world in the field of ICT and digital economy. For this edition of the conference, we have received in total 173 papers whose authors come from over 25 countries around the world. Only 43 papers of the highest quality were selected for oral presentation and publication in this LNNS volume. The average rate of papers accepted by this volume is about 25%. Papers included in these proceedings cover the following topics: data science and artificial intelligence, image and natural language processing, software engineering and information system, network and communications, and digital economy. The accepted and presented papers focus on new trends and challenges facing information technology and its applications. The presenters show how research works can stimulate novel and innovative applications. We hope that you find these results useful and inspiring for your future research work.
The Paradigm Shift To Multimodality In Contemporary Computer Interfaces
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Author : Sharon Oviatt
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
The Paradigm Shift To Multimodality In Contemporary Computer Interfaces written by Sharon Oviatt and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
During the last decade, cell phones with multimodal interfaces based on combined new media have become the dominant computer interface worldwide. Multimodal interfaces support mobility and expand the expressive power of human input to computers. They have shifted the fulcrum of human-computer interaction much closer to the human. This book explains the foundation of human-centered multimodal interaction and interface design, based on the cognitive and neurosciences, as well as the major benefits of multimodal interfaces for human cognition and performance. It describes the data-intensive methodologies used to envision, prototype, and evaluate new multimodal interfaces. From a system development viewpoint, this book outlines major approaches for multimodal signal processing, fusion, architectures, and techniques for robustly interpreting users' meaning. Multimodal interfaces have been commercialized extensively for field and mobile applications during the last decade. Research also is growing rapidly in areas like multimodal data analytics, affect recognition, accessible interfaces, embedded and robotic interfaces, machine learning and new hybrid processing approaches, and similar topics. The expansion of multimodal interfaces is part of the long-term evolution of more expressively powerful input to computers, a trend that will substantially improve support for human cognition and performance. Table of Contents: Preface: Intended Audience and Teaching with this Book / Acknowledgments / Introduction / Definition and Typre of Multimodal Interface / History of Paradigm Shift from Graphical to Multimodal Interfaces / Aims and Advantages of Multimodal Interfaces / Evolutionary, Neuroscience, and Cognitive Foundations of Multimodal Interfaces / Theoretical Foundations of Multimodal Interfaces / Human-Centered Design of Multimodal Interfaces / Multimodal Signal Processing, Fusion, and Architectures / Multimodal Language, Semantic Processing, and Multimodal Integration / Commercialization of Multimodal Interfaces / Emerging Multimodal Research Areas, and Applications / Beyond Multimodality: Designing More Expressively Powerful Interfaces / Conclusions and Future Directions / Bibliography / Author Biographies