Low-Rank Models in Visual Analysis
  • Author : Zhouchen Lin
  • Release Date : 06 June 2017
  • Publisher : Academic Press
  • Genre : Computers
  • Pages : 260
  • ISBN 13 : 9780128127322

Low-Rank Models in Visual Analysis Book Summary

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

Low Rank Models in Visual Analysis

Low Rank Models in Visual Analysis

Author : Zhouchen Lin,Hongyang Zhang
Publisher : Academic Press
Genre : Computers
Total View : 6582 Views
File Size : 45,5 Mb
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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 ...

Low Rank and Sparse Modeling for Visual Analysis

Low Rank and Sparse Modeling for Visual Analysis

Author : Yun Fu
Publisher : Springer
Genre : Computers
Total View : 6265 Views
File Size : 43,5 Mb
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This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, ...

Deep Learning through Sparse and Low Rank Modeling

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Author : Zhangyang Wang,Yun Fu,Thomas S. Huang
Publisher : Academic Press
Genre : Computers
Total View : 5244 Views
File Size : 46,7 Mb
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Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models—those that emphasize problem-specific Interpretability—with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with ...

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Author : Ivan Markovsky
Publisher : Springer
Genre : Technology & Engineering
Total View : 2457 Views
File Size : 41,5 Mb
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This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of ...

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Publisher : Academic Press
Genre : Computers
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File Size : 55,5 Mb
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To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of ...

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Publisher : Academic Press
Genre : Computers
Total View : 8441 Views
File Size : 46,6 Mb
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Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will ...

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Publisher : Academic Press
Genre : Computers
Total View : 8071 Views
File Size : 41,7 Mb
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Spectral Geometry of Shapes presents unique shape analysis approaches based on shape spectrum in differential geometry. It provides insights on how to develop geometry-based methods for 3D shape analysis. The book is an ideal learning resource for graduate students and researchers in computer science, computer engineering and applied mathematics who ...

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Author : Zhen Cui,Jinshan Pan,Shanshan Zhang,Liang Xiao,Jian Yang
Publisher : Springer Nature
Genre : Computers
Total View : 6876 Views
File Size : 42,9 Mb
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The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big ...