Machine Learning In Multimedia
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Machine Learning Techniques For Multimedia
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Author : Matthieu Cord
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-07
Machine Learning Techniques For Multimedia written by Matthieu Cord and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-07 with Computers categories.
Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations – the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply. This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music. This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
Machine Learning For Multimedia Content Analysis
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Author : Yihong Gong
language : en
Publisher: Springer
Release Date : 2010-02-12
Machine Learning For Multimedia Content Analysis written by Yihong Gong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-12 with Computers categories.
This volume introduces machine learning techniques that are particularly powerful and effective for modeling multimedia data and common tasks of multimedia content analysis. It systematically covers key machine learning techniques in an intuitive fashion and demonstrates their applications through case studies. Coverage includes examples of unsupervised learning, generative models and discriminative models. In addition, the book examines Maximum Margin Markov (M3) networks, which strive to combine the advantages of both the graphical models and Support Vector Machines (SVM).
Machine Learning For Intelligent Multimedia Analytics
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Author : Pardeep Kumar
language : en
Publisher: Springer Nature
Release Date : 2021-01-16
Machine Learning For Intelligent Multimedia Analytics written by Pardeep 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 2021-01-16 with Technology & Engineering categories.
This book presents applications of machine learning techniques in processing multimedia large-scale data. Multimedia such as text, image, audio, video, and graphics stands as one of the most demanding and exciting aspects of the information era. The book discusses new challenges faced by researchers in dealing with these large-scale data and also presents innovative solutions to address several potential research problems, e.g., enabling comprehensive visual classification to fill the semantic gap by exploring large-scale data, offering a promising frontier for detailed multimedia understanding, as well as extract patterns and making effective decisions by analyzing the large collection of data.
Automated Machine Learning And Meta Learning For Multimedia
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Author : Wenwu Zhu
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Automated Machine Learning And Meta Learning For Multimedia written by Wenwu Zhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Computers categories.
This book disseminates and promotes the recent research progress and frontier development on AutoML and meta-learning as well as their applications on computer vision, natural language processing, multimedia and data mining related fields. These are exciting and fast-growing research directions in the general field of machine learning. The authors advocate novel, high-quality research findings, and innovative solutions to the challenging problems in AutoML and meta-learning. This topic is at the core of the scope of artificial intelligence, and is attractive to audience from both academia and industry. This book is highly accessible to the whole machine learning community, including: researchers, students and practitioners who are interested in AutoML, meta-learning, and their applications in multimedia, computer vision, natural language processing and data mining related tasks. The book is self-contained and designed for introductory and intermediate audiences. No special prerequisite knowledge is required to read this book.
5g Multimedia Communication
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Author : Zoran S. Bojkovic
language : en
Publisher: CRC Press
Release Date : 2020-10-27
5g Multimedia Communication written by Zoran S. Bojkovic and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-27 with Computers categories.
In bringing to the readers the book 5G Multimedia Communication: Technology, Multiservices and Deployment, the aim is to present current work and direction on the challenging subject of multimedia communications, with theoretical and practical roots. The past two decades have witnessed an extremely fast evolution of mobile cellular network technology. The fifth generation of mobile wireless systems has achieved the first milestone toward finalization and deployment by 2020. This is vital to the development of future multimedia communications. Also, it is necessary to consider 5G technology from the performance point of view by analyzing network capabilities to the operator and to the end user in terms of data rate, capacity, coverage, energy efficiency, connectivity and latency. The book is divided into three major parts with each part containing four to seven chapters: • Critical enabling technology • Multiservices network • Deployment scenarios The first part discusses enabling technologies, such as green communication, channel modeling, massive and distributed MIMO and ML-based networks. In the second part, different methodologies and standards for multiservices have been discussed. Exclusive chapters have been dedicated to each of the open research challenges such as multimedia operating in 5G environment, network slicing optimization, mobile edge computing, mobile video multicast/broadcast, integrated satellite and drone communication. The third part paved the way to deployment scenarios for different innovative services including integration of a multienergy system in smart cities, intelligent transportation systems, 5G connectivity in the transport sector, healthcare services, 5G edge-based video surveillance and challenges of connectivity for massive IoT in 5G and beyond systems. The book is written by experts in the field who introduced scientific and engineering concepts, covering the 5G multimedia communication areas. The book can be read cover-to-cover or selectively in the areas of interest for the readers. Generally, the book is intended for novel readers who could benefit from understanding general concepts, practitioners who seek guidance into the field and senior-level as well as graduate-level engineering students in understanding the process of today’s wireless multimedia communications.
Deep Learning For Multimedia Forensics
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Author : Irene Amerini
language : en
Publisher:
Release Date : 2021-08-31
Deep Learning For Multimedia Forensics written by Irene Amerini and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-31 with Computers categories.
In this survey, the latest trends and deep-learning-based techniques for multimedia forensics are introduced, in both architectural and data-processing. The publication is intended for researchers, students and professionals active in the fields of Deep Learning and Multimedia Forensics.
Machine Learning For Multimedia Content Analysis
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Author : Yihong Gong
language : en
Publisher: Springer-Verlag New York Incorporated
Release Date : 2007-10-01
Machine Learning For Multimedia Content Analysis written by Yihong Gong and has been published by Springer-Verlag New York Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-01 with Computers categories.
This volume introduces machine learning techniques that are particularly effective for modeling multimedia data and common tasks of multimedia content analysis. It demonstrates the application of key machine learning techniques through case studies.
Challenges And Applications For Implementing Machine Learning In Computer Vision
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Author : Kashyap, Ramgopal
language : en
Publisher: IGI Global
Release Date : 2019-10-04
Challenges And Applications For Implementing Machine Learning In Computer Vision written by Kashyap, Ramgopal and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-04 with Computers categories.
Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.
Multimedia Technology And Enhanced Learning
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Author : Weina Fu
language : en
Publisher: Springer
Release Date : 2021-07-23
Multimedia Technology And Enhanced Learning written by Weina Fu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-23 with Computers categories.
This two-volume book constitutes the refereed proceedings of the 3rd International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021, held in April 2021. Due to the COVID-19 pandemic the conference was held virtually. The 97 revised full papers have been selected from 208 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Multi Faceted Deep Learning
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Author : Jenny Benois-Pineau
language : en
Publisher: Springer Nature
Release Date : 2021-10-20
Multi Faceted Deep Learning written by Jenny Benois-Pineau and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-20 with Computers categories.
This book covers a large set of methods in the field of Artificial Intelligence - Deep Learning applied to real-world problems. The fundamentals of the Deep Learning approach and different types of Deep Neural Networks (DNNs) are first summarized in this book, which offers a comprehensive preamble for further problem–oriented chapters. The most interesting and open problems of machine learning in the framework of Deep Learning are discussed in this book and solutions are proposed. This book illustrates how to implement the zero-shot learning with Deep Neural Network Classifiers, which require a large amount of training data. The lack of annotated training data naturally pushes the researchers to implement low supervision algorithms. Metric learning is a long-term research but in the framework of Deep Learning approaches, it gets freshness and originality. Fine-grained classification with a low inter-class variability is a difficult problem for any classification tasks. This book presents how it is solved, by using different modalities and attention mechanisms in 3D convolutional networks. Researchers focused on Machine Learning, Deep learning, Multimedia and Computer Vision will want to buy this book. Advanced level students studying computer science within these topic areas will also find this book useful.