Multiview Machine Learning

Multiview Machine Learning
Author: Shiliang Sun
Publisher: Springer
Total Pages: 149
Release: 2019-01-07
Genre: Computers
ISBN: 9811330298
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This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This book describes the models and algorithms of multiview learning in real data analysis. Incorporating multiple views to improve the generalization performance, multiview learning is also known as data fusion or data integration from multiple feature sets. This self-contained book is applicable for multi-modal learning research, and requires minimal prior knowledge of the basic concepts in the field. It is also a valuable reference resource for researchers working in the field of machine learning and also those in various application domains.

Multi-View Stereo

Multi-View Stereo
Author: Yasutaka Furukawa
Publisher: Foundations and Trends (R) in Computer Graphics and Vision
Total Pages: 166
Release: 2015-06-25
Genre: Computer algorithms
ISBN: 9781601988362
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Presents a hands-on view of the field of multi-view stereo with a focus on practical algorithms. It frames the multiview stereo problem as an image/geometry consistency optimization problem and describesits main two ingredients: robust implementations of photometric consistency measures and efficient optimization algorithms.

Linking and Mining Heterogeneous and Multi-view Data

Linking and Mining Heterogeneous and Multi-view Data
Author: Deepak P
Publisher: Springer
Total Pages: 343
Release: 2018-12-13
Genre: Technology & Engineering
ISBN: 3030018725
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This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, with an emphasis on exploratory and unsupervised data analysis, an area of increasing significance with the pace of growth of data vastly outpacing any chance of labeling them manually. The book looks at the underlying algorithms and technologies that facilitate the area within big data analytics, it covers their applications across domains such as smarter transportation, social media, fake news detection and enterprise search among others. This book enables readers to understand a spectrum of advances in this emerging area, and it will hopefully empower them to leverage and develop methods in multi-source data fusion and analytics with applications to a variety of scenarios. Includes advances on unsupervised, semi-supervised and supervised approaches to heterogeneous data linkage and fusion; Covers use cases of analytics over multi-view and heterogeneous data from across a variety of domains such as fake news, smarter transportation and social media, among others; Provides a high-level overview of advances in this emerging field and empowers the reader to explore novel applications and methodologies that would enrich the field.

Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms

Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms
Author: Management Association, Information Resources
Publisher: IGI Global
Total Pages: 1534
Release: 2020-12-05
Genre: Computers
ISBN: 1799880990
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Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.

Multi-dimensional Imaging

Multi-dimensional Imaging
Author: Bahram Javidi
Publisher: John Wiley & Sons
Total Pages: 524
Release: 2014-03-26
Genre: Technology & Engineering
ISBN: 1118705742
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Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field Multi-dimensional Imaging takes the reader from the introductory concepts through to the latest applications of these techniques. Split into 3 parts covering 3D image capture, processing, visualization and display, using 1) a Multi-View Approach and 2.) a Holographic Approach, followed by a 3rd part addressing other 3D systems approaches, applications and signal processing for advanced 3D imaging. This book describes recent developments, as well as the prospects and challenges in advances in imaging sciences and engineering such as 3D image sensing, 3D holographic imaging, imaging applications for bio-photonics and 3D image recognition. Advanced imaging systems incorporate knowledge from various fields. It is a complex technology that combines physics, optics, signal processing, and image capture techniques. Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field. Integrates the background, introductory material with new advances in 3D imaging and applications. Covers the most recent technologies such as high speed digital holography, compressive sensing, real-time 3D integral imaging, 3D TV, photon counting imaging. To be available as an enhanced ebook with added functionality of colour films showing the effects of advanced 3D applications such as 3D microscopy, 3D biomedical imaging and 3D for security and defense applications. Acts as a single source reference to the rapidly developing field of 3D imaging technology. Provides supplementary material on a companion website including video clips, examples, numerical simulations, and experimental results to show the theoretical concepts. With contributions from leading researchers from across these fields, Multi-dimensional Imaging is a comprehensive reference for the imaging technology research community.

Multi-aspect Learning

Multi-aspect Learning
Author: Richi Nayak
Publisher: Springer Nature
Total Pages: 191
Release: 2023-08-28
Genre: Computers
ISBN: 3031335600
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This book offers a detailed and comprehensive analysis of multi-aspect data learning, focusing especially on representation learning approaches for unsupervised machine learning. It covers state-of-the-art representation learning techniques for clustering and their applications in various domains. This is the first book to systematically review multi-aspect data learning, incorporating a range of concepts and applications. Additionally, it is the first to comprehensively investigate manifold learning for dimensionality reduction in multi-view data learning. The book presents the latest advances in matrix factorization, subspace clustering, spectral clustering and deep learning methods, with a particular emphasis on the challenges and characteristics of multi-aspect data. Each chapter includes a thorough discussion of state-of-the-art of multi-aspect data learning methods and important research gaps. The book provides readers with the necessary foundational knowledge to apply these methods to new domains and applications, as well as inspire new research in this emerging field.

Learning Representation for Multi-View Data Analysis

Learning Representation for Multi-View Data Analysis
Author: Zhengming Ding
Publisher: Springer
Total Pages: 272
Release: 2018-12-06
Genre: Computers
ISBN: 3030007340
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This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.

Multi-Camera Networks

Multi-Camera Networks
Author: Hamid Aghajan
Publisher: Academic Press
Total Pages: 623
Release: 2009-04-25
Genre: Technology & Engineering
ISBN: 0080878008
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The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware This book is the definitive reference in multi-camera networks. It gives clear guidance on the conceptual and implementation issues involved in the design and operation of multi-camera networks, as well as presenting the state-of-the-art in hardware, algorithms and system development. The book is broad in scope, covering smart camera architectures, embedded processing, sensor fusion and middleware, calibration and topology, network-based detection and tracking, and applications in distributed and collaborative methods in camera networks. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal and video processing, computer vision, and sensor networks. Hamid Aghajan is a Professor of Electrical Engineering (consulting) at Stanford University. His research is on multi-camera networks for smart environments with application to smart homes, assisted living and well being, meeting rooms, and avatar-based communication and social interactions. He is Editor-in-Chief of Journal of Ambient Intelligence and Smart Environments, and was general chair of ACM/IEEE ICDSC 2008. Andrea Cavallaro is Reader (Associate Professor) at Queen Mary, University of London (QMUL). His research is on target tracking and audiovisual content analysis for advanced surveillance and multi-sensor systems. He serves as Associate Editor of the IEEE Signal Processing Magazine and the IEEE Trans. on Multimedia, and has been general chair of IEEE AVSS 2007, ACM/IEEE ICDSC 2009 and BMVC 2009. The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware

Multiple View Geometry in Computer Vision

Multiple View Geometry in Computer Vision
Author: Richard Hartley
Publisher: Cambridge University Press
Total Pages: 676
Release: 2004-03-25
Genre: Computers
ISBN: 1139449141
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A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.