Handbook Of Robust Low Rank And Sparse Matrix Decomposition

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Handbook of Robust Low-Rank and Sparse Matrix Decomposition

Author : Thierry Bouwmans
Publisher : CRC Press
ISBN 13 : 1315353539
Total Pages : 510 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Handbook of Robust Low-Rank and Sparse Matrix Decomposition by : Thierry Bouwmans

Download or read book Handbook of Robust Low-Rank and Sparse Matrix Decomposition written by Thierry Bouwmans and published by CRC Press. This book was released on 2016-09-20 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.

Handbook of Robust Low-Rank and Sparse Matrix Decomposition

Author : Thierry Bouwmans
Publisher : CRC Press
ISBN 13 : 1498724639
Total Pages : 553 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Handbook of Robust Low-Rank and Sparse Matrix Decomposition by : Thierry Bouwmans

Download or read book Handbook of Robust Low-Rank and Sparse Matrix Decomposition written by Thierry Bouwmans and published by CRC Press. This book was released on 2016-05-27 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.

Proceedings of 2017 Chinese Intelligent Systems Conference

Author : Yingmin Jia
Publisher : Springer
ISBN 13 : 9811064997
Total Pages : 762 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Proceedings of 2017 Chinese Intelligent Systems Conference by : Yingmin Jia

Download or read book Proceedings of 2017 Chinese Intelligent Systems Conference written by Yingmin Jia and published by Springer. This book was released on 2017-09-27 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected research papers from CISC’17, held in MudanJiang, China. The topics covered include Multi-agent system, Evolutionary Computation, Artificial Intelligence, Complex systems, Computation intelligence and soft computing, Intelligent control, Advanced control technology, Robotics and applications, Intelligent information processing, Iterative learning control, Machine Learning, and etc. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

Proceedings of 2018 Chinese Intelligent Systems Conference

Author : Yingmin Jia
Publisher : Springer
ISBN 13 : 9811322910
Total Pages : 844 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Proceedings of 2018 Chinese Intelligent Systems Conference by : Yingmin Jia

Download or read book Proceedings of 2018 Chinese Intelligent Systems Conference written by Yingmin Jia and published by Springer. This book was released on 2018-10-03 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings present selected research papers from CISC’18, held in Wenzhou, China. The topics include Multi-Agent Systems, Networked Control Systems, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Nonlinear and Variable Structure Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles, and so on. Engineers and researchers from academia, industry, and government can get an insight view of the solutions combining ideas from multiple disciplines in the field of intelligent systems.

Low-Rank Models in Visual Analysis

Author : Zhouchen Lin
Publisher : Academic Press
ISBN 13 : 0128127325
Total Pages : 262 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Low-Rank Models in Visual Analysis by : Zhouchen Lin

Download or read book Low-Rank Models in Visual Analysis written by Zhouchen Lin and published by Academic Press. This book was released on 2017-06-06 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. It provides insight into the ideas behind the models and their algorithms, giving details of their formulation and deduction. The main applications included are video denoising, background modeling, image alignment and rectification, motion segmentation, image segmentation and image saliency detection. Readers will learn which Low-rank models are highly useful in practice (both linear and nonlinear models), how to solve low-rank models efficiently, and how to apply low-rank models to real problems. Presents a self-contained, up-to-date introduction that covers underlying theory, algorithms and the state-of-the-art in current applications Provides a full and clear explanation of the theory behind the models Includes detailed proofs in the appendices

Intelligence Science and Big Data Engineering

Author : Yi Sun
Publisher : Springer
ISBN 13 : 3319677772
Total Pages : 691 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Intelligence Science and Big Data Engineering by : Yi Sun

Download or read book Intelligence Science and Big Data Engineering written by Yi Sun and published by Springer. This book was released on 2017-09-14 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2017, held in Dalian, China, in September 2017.The 48 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 121 submissions. They deal with statistics and learning; deep neural networks; faces and people; objects; classification and clustering; imaging; biomedical signal processing; and recommendation.

Machine Learning and Knowledge Discovery in Databases. Research Track

Author : Nuria Oliver
Publisher : Springer Nature
ISBN 13 : 3030865231
Total Pages : 857 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases. Research Track by : Nuria Oliver

Download or read book Machine Learning and Knowledge Discovery in Databases. Research Track written by Nuria Oliver and published by Springer Nature. This book was released on 2021-09-10 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications. Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety. Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics. Applied Data Science Track: Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation. Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.

Computer Vision and Internet of Things

Author : Lavanya Sharma
Publisher : CRC Press
ISBN 13 : 100057055X
Total Pages : 319 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Computer Vision and Internet of Things by : Lavanya Sharma

Download or read book Computer Vision and Internet of Things written by Lavanya Sharma and published by CRC Press. This book was released on 2022-05-19 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Vision and Internet of Things: Technologies and Applications explores the utilization of Internet of Things (IoT) with computer vision and its underlying technologies in different applications areas. Using a series of present and future applications – including business insights, indoor-outdoor securities, smart grids, human detection and tracking, intelligent traffic monitoring, e-health departments, and medical imaging – this book focuses on providing a detailed description of the utilization of IoT with computer vision and its underlying technologies in critical application areas, such as smart grids, emergency departments, intelligent traffic cams, insurance, and the automotive industry. Key Features • Covers the challenging issues related to sensors, detection, and tracking of moving objects with solutions to handle relevant challenges • Describes the latest technological advances in IoT and computer vision with their implementations • Combines image processing and analysis into a unified framework to understand both IOT and computer vision applications • Explores mining and tracking of motion-based object data, such as trajectory prediction and prediction of a particular location of object data, and their critical applications • Provides novel solutions for medical imaging (skin lesion detection, cancer detection, enhancement techniques for MRI images, and automated disease prediction) This book is primarily aimed at graduates and researchers working in the areas of IoT, computer vision, big data, cloud computing, and remote sensing. It is also an ideal resource for IT professionals and technology developers.

Data Science

Author : Carlos Alberto De Bragança Pereira
Publisher : MDPI
ISBN 13 : 3036507922
Total Pages : 256 pages
Book Rating : 4.0/5 (365 download)

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Book Synopsis Data Science by : Carlos Alberto De Bragança Pereira

Download or read book Data Science written by Carlos Alberto De Bragança Pereira and published by MDPI. This book was released on 2021-09-02 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increase in data processing and storage capacity, a large amount of data is available. Data without analysis does not have much value. Thus, the demand for data analysis is increasing daily, and the consequence is the appearance of a large number of jobs and published articles. Data science has emerged as a multidisciplinary field to support data-driven activities, integrating and developing ideas, methods, and processes to extract information from data. This includes methods built from different knowledge areas: Statistics, Computer Science, Mathematics, Physics, Information Science, and Engineering. This mixture of areas has given rise to what we call Data Science. New solutions to the new problems are reproducing rapidly to generate large volumes of data. Current and future challenges require greater care in creating new solutions that satisfy the rationality for each type of problem. Labels such as Big Data, Data Science, Machine Learning, Statistical Learning, and Artificial Intelligence are demanding more sophistication in the foundations and how they are being applied. This point highlights the importance of building the foundations of Data Science. This book is dedicated to solutions and discussions of measuring uncertainties in data analysis problems.

Robust Latent Feature Learning for Incomplete Big Data

Author : Di Wu
Publisher : Springer Nature
ISBN 13 : 981198140X
Total Pages : 119 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Robust Latent Feature Learning for Incomplete Big Data by : Di Wu

Download or read book Robust Latent Feature Learning for Incomplete Big Data written by Di Wu and published by Springer Nature. This book was released on 2022-12-06 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete big data due to its high accuracy, computational efficiency, and ease of scalability. The crux of analyzing incomplete big data lies in addressing the uncertainty problem caused by their incomplete characteristics. However, existing LFA methods do not fully consider such uncertainty. In this book, the author introduces several robust latent feature learning methods to address such uncertainty for effectively and efficiently analyzing incomplete big data, including robust latent feature learning based on smooth L1-norm, improving robustness of latent feature learning using L1-norm, improving robustness of latent feature learning using double-space, data-characteristic-aware latent feature learning, posterior-neighborhood-regularized latent feature learning, and generalized deep latent feature learning. Readers can obtain an overview of the challenges of analyzing incomplete big data and how to employ latent feature learning to build a robust model to analyze incomplete big data. In addition, this book provides several algorithms and real application cases, which can help students, researchers, and professionals easily build their models to analyze incomplete big data.

Towards Smart World

Author : Lavanya Sharma
Publisher : CRC Press
ISBN 13 : 1000284956
Total Pages : 396 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Towards Smart World by : Lavanya Sharma

Download or read book Towards Smart World written by Lavanya Sharma and published by CRC Press. This book was released on 2020-12-13 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Towards Smart World: Homes to Cities Using Internet of Things provides an overview of basic concepts from the rising of machines and communication to IoT for making cities smart, real-time applications domains, related technologies, and their possible solutions for handling relevant challenges. This book highlights the utilization of IoT for making cities smart and its underlying technologies in real-time application areas such as emergency departments, intelligent traffic systems, indoor and outdoor securities, automotive industries, environmental monitoring, business entrepreneurship, facial recognition, and motion-based object detection. Features The book covers the challenging issues related to sensors, detection, and tracking of moving objects, and solutions to handle relevant challenges. It contains the most recent research analysis in the domain of communications, signal processing, and computing sciences for facilitating smart homes, buildings, environmental conditions, and cities. It presents the readers with practical approaches and future direction for using IoT in smart cities and discusses how it deals with human dynamics, the ecosystem, and social objects and their relation. It describes the latest technological advances in IoT and visual surveillance with their implementations. This book is an ideal resource for IT professionals, researchers, undergraduate or postgraduate students, practitioners, and technology developers who are interested in gaining deeper knowledge and implementing IoT for smart cities, real-time applications areas, and technologies, and a possible set of solutions to handle relevant challenges. Dr. Lavanya Sharma is an Assistant Professor in the Amity Institute of Information Technology at Amity University UP, Noida, India. She has been a recipient of several prestigious awards during her academic career. She is an active nationally recognized researcher who has published numerous papers in her field.

Advances in Computer Graphics

Author : Bin Sheng
Publisher : Springer Nature
ISBN 13 : 3031500784
Total Pages : 409 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Advances in Computer Graphics by : Bin Sheng

Download or read book Advances in Computer Graphics written by Bin Sheng and published by Springer Nature. This book was released on 2024-01-24 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 4-volume set of LNCS 14495-14498 constitutes the proceedings of the 40th Computer Graphics International Conference, CGI 2023, held in Shanghai, China, August 28 – September 1, 2023. The 149 papers in this set were carefully reviewed and selected from 385 submissions. They are organized in topical sections as follows: Detection and Recognition; Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception; Reconstruction; Rendering and Animation; Synthesis and Generation; Visual Analytics and Modeling; Graphics and AR/VR; Medical Imaging and Robotics; Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology; Empowering Novel Geometric Algebra for Graphics and Engineering.

Scalable Low-rank Matrix and Tensor Decomposition on Graphs

Author : Nauman Shahid
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Scalable Low-rank Matrix and Tensor Decomposition on Graphs by : Nauman Shahid

Download or read book Scalable Low-rank Matrix and Tensor Decomposition on Graphs written by Nauman Shahid and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Mots-clés de l'auteur: Principal Component Analysis ; graphs ; low-rank and sparse decomposition ; clustering ; low-rank tensors.

Provable Algorithms for Scalable and Robust Low-rank Matrix Recovery

Author : Yuanxin Li (Ph. D. in electrical and computer engineering)
Publisher :
ISBN 13 :
Total Pages : 143 pages
Book Rating : 4.:/5 (19 download)

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Book Synopsis Provable Algorithms for Scalable and Robust Low-rank Matrix Recovery by : Yuanxin Li (Ph. D. in electrical and computer engineering)

Download or read book Provable Algorithms for Scalable and Robust Low-rank Matrix Recovery written by Yuanxin Li (Ph. D. in electrical and computer engineering) and published by . This book was released on 2018 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Low-rank models are ubiquitous in a wide range of practical applications, and low-rank matrix sensing and recovery has become a problem of great importance. Via leveraging the low-rank structure in data representations, it is possible to faithfully recover the matrix of interest from incomplete observations, in both statistically and computationally efficient manners. This dissertation investigates the fundamental problem of low-rank matrix recovery in different random measurement models, possibly with corruptions.

A Supervised Low-rank Matrix Decomposition for Matching

Author : Sajid Sharlemin
Publisher :
ISBN 13 :
Total Pages : 39 pages
Book Rating : 4.:/5 (942 download)

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Book Synopsis A Supervised Low-rank Matrix Decomposition for Matching by : Sajid Sharlemin

Download or read book A Supervised Low-rank Matrix Decomposition for Matching written by Sajid Sharlemin and published by . This book was released on 2014 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Variational Methods for Nonlinear Geometric Data

Author : Philipp Grohs
Publisher : Springer Nature
ISBN 13 : 3030313514
Total Pages : 701 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Handbook of Variational Methods for Nonlinear Geometric Data by : Philipp Grohs

Download or read book Handbook of Variational Methods for Nonlinear Geometric Data written by Philipp Grohs and published by Springer Nature. This book was released on 2020-04-03 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers different, current research directions in the context of variational methods for non-linear geometric data. Each chapter is authored by leading experts in the respective discipline and provides an introduction, an overview and a description of the current state of the art. Non-linear geometric data arises in various applications in science and engineering. Examples of nonlinear data spaces are diverse and include, for instance, nonlinear spaces of matrices, spaces of curves, shapes as well as manifolds of probability measures. Applications can be found in biology, medicine, product engineering, geography and computer vision for instance. Variational methods on the other hand have evolved to being amongst the most powerful tools for applied mathematics. They involve techniques from various branches of mathematics such as statistics, modeling, optimization, numerical mathematics and analysis. The vast majority of research on variational methods, however, is focused on data in linear spaces. Variational methods for non-linear data is currently an emerging research topic. As a result, and since such methods involve various branches of mathematics, there is a plethora of different, recent approaches dealing with different aspects of variational methods for nonlinear geometric data. Research results are rather scattered and appear in journals of different mathematical communities. The main purpose of the book is to account for that by providing, for the first time, a comprehensive collection of different research directions and existing approaches in this context. It is organized in a way that leading researchers from the different fields provide an introductory overview of recent research directions in their respective discipline. As such, the book is a unique reference work for both newcomers in the field of variational methods for non-linear geometric data, as well as for established experts that aim at to exploit new research directions or collaborations. Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com.

On Low-rank Updates to the Singular Value and Tucker Decompositions

Author :
Publisher :
ISBN 13 :
Total Pages : 9 pages
Book Rating : 4.:/5 (727 download)

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Book Synopsis On Low-rank Updates to the Singular Value and Tucker Decompositions by :

Download or read book On Low-rank Updates to the Singular Value and Tucker Decompositions written by and published by . This book was released on 2009 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: The singular value decomposition is widely used in signal processing and data mining. Since the data often arrives in a stream, the problem of updating matrix decompositions under low-rank modification has been widely studied. Brand developed a technique in 2006 that has many advantages. However, the technique does not directly approximate the updated matrix, but rather its previous low-rank approximation added to the new update, which needs justification. Further, the technique is still too slow for large information processing problems. We show that the technique minimizes the change in error per update, so if the error is small initially it remains small. We show that an updating algorithm for large sparse matrices should be sub-linear in the matrix dimension in order to be practical for large problems, and demonstrate a simple modification to the original technique that meets the requirements.