Sparse Representation Modeling And Learning In Visual Recognition PDF Download
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Author | : Hong Cheng |
Publisher | : Springer |
Total Pages | : 259 |
Release | : 2015-05-25 |
Genre | : Computers |
ISBN | : 1447167147 |
Download Sparse Representation, Modeling and Learning in Visual Recognition Book in PDF, ePub and Kindle
This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition; covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers; discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning; includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book.
Author | : Zhangyang Wang |
Publisher | : Academic Press |
Total Pages | : 296 |
Release | : 2019-04-26 |
Genre | : Computers |
ISBN | : 0128136596 |
Download Deep Learning through Sparse and Low-Rank Modeling Book in PDF, ePub and Kindle
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 the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics. Combines classical sparse and low-rank models and algorithms with the latest advances in deep learning networks Shows how the structure and algorithms of sparse and low-rank methods improves the performance and interpretability of Deep Learning models Provides tactics on how to build and apply customized deep learning models for various applications
Author | : Jayaraman J. Thiagarajan |
Publisher | : Springer Nature |
Total Pages | : 115 |
Release | : 2022-06-01 |
Genre | : Technology & Engineering |
ISBN | : 3031022505 |
Download Image Understanding using Sparse Representations Book in PDF, ePub and Kindle
Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blind source separation, super-resolution, and classification. The primary goal of this book is to present the theory and algorithmic considerations in using sparse models for image understanding and computer vision applications. To this end, algorithms for obtaining sparse representations and their performance guarantees are discussed in the initial chapters. Furthermore, approaches for designing overcomplete, data-adapted dictionaries to model natural images are described. The development of theory behind dictionary learning involves exploring its connection to unsupervised clustering and analyzing its generalization characteristics using principles from statistical learning theory. An exciting application area that has benefited extensively from the theory of sparse representations is compressed sensing of image and video data. Theory and algorithms pertinent to measurement design, recovery, and model-based compressed sensing are presented. The paradigm of sparse models, when suitably integrated with powerful machine learning frameworks, can lead to advances in computer vision applications such as object recognition, clustering, segmentation, and activity recognition. Frameworks that enhance the performance of sparse models in such applications by imposing constraints based on the prior discriminatory information and the underlying geometrical structure, and kernelizing the sparse coding and dictionary learning methods are presented. In addition to presenting theoretical fundamentals in sparse learning, this book provides a platform for interested readers to explore the vastly growing application domains of sparse representations.
Author | : Julien Mairal |
Publisher | : Now Publishers |
Total Pages | : 216 |
Release | : 2014-12-19 |
Genre | : Computers |
ISBN | : 9781680830088 |
Download Sparse Modeling for Image and Vision Processing Book in PDF, ePub and Kindle
Sparse Modeling for Image and Vision Processing offers a self-contained view of sparse modeling for visual recognition and image processing. More specifically, it focuses on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.
Author | : Anders Heyden |
Publisher | : Springer |
Total Pages | : 0 |
Release | : 2002-05-17 |
Genre | : Computers |
ISBN | : 9783540437482 |
Download Computer Vision - ECCV 2002 Book in PDF, ePub and Kindle
Premiering in 1990 in Antibes, France, the European Conference on Computer Vision, ECCV, has been held biennially at venues all around Europe. These conferences have been very successful, making ECCV a major event to the computer vision community. ECCV 2002 was the seventh in the series. The privilege of organizing it was shared by three universities: The IT University of Copenhagen, the University of Copenhagen, and Lund University, with the conference venue in Copenhagen. These universities lie ̈ geographically close in the vivid Oresund region, which lies partly in Denmark and partly in Sweden, with the newly built bridge (opened summer 2000) crossing the sound that formerly divided the countries. We are very happy to report that this year’s conference attracted more papers than ever before, with around 600 submissions. Still, together with the conference board, we decided to keep the tradition of holding ECCV as a single track conference. Each paper was anonymously refereed by three different reviewers. For the nal selection, for the rst time for ECCV, a system with area chairs was used. These met with the program chairsinLundfortwodaysinFebruary2002toselectwhatbecame45oralpresentations and 181 posters.Also at this meeting the selection was made without knowledge of the authors’identity.
Author | : Zhaowen E. T. Al WANG |
Publisher | : World Scientific |
Total Pages | : 239 |
Release | : 2015-10-28 |
Genre | : Computers |
ISBN | : 9814725056 |
Download Sparse Coding and Its Applications in Computer Vision Book in PDF, ePub and Kindle
"This book provides a broader introduction to the theories and applications of sparse coding techniques in computer vision research. It introduces sparse coding in the context of representation learning, illustrates the fundamental concepts, and summarizes the most active research directions. A variety of applications of sparse coding are discussed, ranging from low-level image processing tasks such as super-resolution and de-blurring to high-level semantic understanding tasks such as image recognition, clustering and fusion. The book is suitable to be used as an introductory overview to this field, with its theoretical part being both easy and precious enough for quick understanding. It is also of great value to experienced researchers as it offers new perspective to the underlying mechanism of sparse coding, and points out potential future directions for different applications."--
Author | : Yun Fu |
Publisher | : Springer |
Total Pages | : 240 |
Release | : 2014-10-30 |
Genre | : Computers |
ISBN | : 331912000X |
Download Low-Rank and Sparse Modeling for Visual Analysis Book in PDF, ePub and Kindle
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, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.
Author | : Joseph F. Murray |
Publisher | : |
Total Pages | : 412 |
Release | : 2005 |
Genre | : |
ISBN | : |
Download Visual Recognition, Inference and Coding Using Learned Sparse Overcomplete Representations Book in PDF, ePub and Kindle
Author | : Jean-Daniel Boissonnat |
Publisher | : Springer |
Total Pages | : 758 |
Release | : 2012-01-06 |
Genre | : Computers |
ISBN | : 3642274137 |
Download Curves and Surfaces Book in PDF, ePub and Kindle
This volume constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Curves and Surfaces, held in Avignon, in June 2010. The conference had the overall theme: "Representation and Approximation of Curves and Surfaces and Applications". The 39 revised full papers presented together with 9 invited talks were carefully reviewed and selected from 114 talks presented at the conference. The topics addressed by the papers range from mathematical foundations to practical implementation on modern graphics processing units and address a wide area of topics such as computer-aided geometric design, computer graphics and visualisation, computational geometry and topology, geometry processing, image and signal processing, interpolation and smoothing, scattered data processing and learning theory and subdivision, wavelets and multi-resolution methods.
Author | : Andrew Fitzgibbon |
Publisher | : Springer |
Total Pages | : 909 |
Release | : 2012-09-26 |
Genre | : Computers |
ISBN | : 3642337090 |
Download Computer Vision – ECCV 2012 Book in PDF, ePub and Kindle
The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.