Sparse Modeling With Universal Priors And Learned Incoherent Dictionaries Preprint
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Sparse Modeling With Universal Priors And Learned Incoherent Dictionaries Preprint
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Author :
language : en
Publisher:
Release Date : 2009
Sparse Modeling With Universal Priors And Learned Incoherent Dictionaries Preprint written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Sparse data models have gained considerable attention in recent years, and their use has led to state-of-the-art results in many signal and image processing tasks. The learning of sparse models has been mostly concerned with adapting the dictionary to tasks such as classification and reconstruction, optimizing extrinsic properties of the trained dictionaries. In this work, we first propose a learning method aimed at enhancing both extrinsic and intrinsic properties of the dictionaries, such as the mutual and cumulative coherence and the Gram matrix norm, characteristics known to improve the efficiency and performance of sparse coding algorithms. We then use tools from information theory to propose a sparsity regularization term which has several desirable theoretical and practical advantages over the more standard '0 or '1 ones. These new sparse modeling components lead to improved coding performance and accuracy in reconstruction tasks.
Sparse Modeling For Image And Vision Processing
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Author : Julien Mairal
language : en
Publisher: Now Publishers
Release Date : 2014-12-19
Sparse Modeling For Image And Vision Processing written by Julien Mairal and has been published by Now Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-19 with Computers categories.
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.
An Invitation To 3 D Vision
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Author : Yi Ma
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-06
An Invitation To 3 D Vision written by Yi Ma 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 2012-11-06 with Computers categories.
This book introduces the geometry of 3-D vision, that is, the reconstruction of 3-D models of objects from a collection of 2-D images. It details the classic theory of two view geometry and shows that a more proper tool for studying the geometry of multiple views is the so-called rank consideration of the multiple view matrix. It also develops practical reconstruction algorithms and discusses possible extensions of the theory.
Sparse And Redundant Representations
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Author : Michael Elad
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-12
Sparse And Redundant Representations written by Michael Elad 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 2010-08-12 with Mathematics categories.
A long long time ago, echoing philosophical and aesthetic principles that existed since antiquity, William of Ockham enounced the principle of parsimony, better known today as Ockham’s razor: “Entities should not be multiplied without neces sity. ” This principle enabled scientists to select the ”best” physical laws and theories to explain the workings of the Universe and continued to guide scienti?c research, leadingtobeautifulresultsliketheminimaldescriptionlength approachtostatistical inference and the related Kolmogorov complexity approach to pattern recognition. However, notions of complexity and description length are subjective concepts anddependonthelanguage“spoken”whenpresentingideasandresults. The?eldof sparse representations, that recently underwent a Big Bang like expansion, explic itly deals with the Yin Yang interplay between the parsimony of descriptions and the “language” or “dictionary” used in them, and it became an extremely exciting area of investigation. It already yielded a rich crop of mathematically pleasing, deep and beautiful results that quickly translated into a wealth of practical engineering applications. You are holding in your hands the ?rst guide book to Sparseland, and I am sure you’ll ?nd in it both familiar and new landscapes to see and admire, as well as ex cellent pointers that will help you ?nd further valuable treasures. Enjoy the journey to Sparseland! Haifa, Israel, December 2009 Alfred M. Bruckstein vii Preface This book was originally written to serve as the material for an advanced one semester (fourteen 2 hour lectures) graduate course for engineering students at the Technion, Israel.
The Sparse Fourier Transform
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Author : Haitham Hassanieh
language : en
Publisher: Morgan & Claypool
Release Date : 2018-02-27
The Sparse Fourier Transform written by Haitham Hassanieh and has been published by Morgan & Claypool this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-27 with Computers categories.
The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary. This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits. This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.
A Theory Of Shape Identification
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Author : Frédéric Cao
language : en
Publisher: Springer
Release Date : 2008-08-17
A Theory Of Shape Identification written by Frédéric Cao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-17 with Mathematics categories.
Recent years have seen dramatic progress in shape recognition algorithms applied to ever-growing image databases. They have been applied to image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability of humans and animals to detect and recognize shapes is one of the enigmas of perception. The book describes a complete method that starts from a query image and an image database and yields a list of the images in the database containing shapes present in the query image. A false alarm number is associated to each detection. Many experiments will show that familiar simple shapes or images can reliably be identified with false alarm numbers ranging from 10-5 to less than 10-300. Technically speaking, there are two main issues. The first is extracting invariant shape descriptors from digital images. Indeed, a shape can be seen from various angles and distances and in various lights.
Machine Learning For Medical Image Reconstruction
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Author : Florian Knoll
language : en
Publisher: Springer Nature
Release Date : 2019-10-24
Machine Learning For Medical Image Reconstruction written by Florian Knoll and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-24 with Computers categories.
This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 24 full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography; and deep learning for general image reconstruction.
The Principles Of Deep Learning Theory
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Author : Daniel A. Roberts
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-26
The Principles Of Deep Learning Theory written by Daniel A. Roberts and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-26 with Computers categories.
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Digital Signal Processing With Matlab Examples Volume 3
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Author : Jose Maria Giron-Sierra
language : en
Publisher: Springer
Release Date : 2016-11-21
Digital Signal Processing With Matlab Examples Volume 3 written by Jose Maria Giron-Sierra and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Technology & Engineering categories.
This is the third volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book primarily focuses on filter banks, wavelets, and images. While the Fourier transform is adequate for periodic signals, wavelets are more suitable for other cases, such as short-duration signals: bursts, spikes, tweets, lung sounds, etc. Both Fourier and wavelet transforms decompose signals into components. Further, both are also invertible, so the original signals can be recovered from their components. Compressed sensing has emerged as a promising idea. One of the intended applications is networked devices or sensors, which are now becoming a reality; accordingly, this topic is also addressed. A selection of experiments that demonstrate image denoising applications are also included. In the interest of reader-friendliness, the longer programs have been grouped in an appendix; further, a second appendix on optimization has been added to supplement the content of the last chapter.
Machine Audition Principles Algorithms And Systems
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Author : Wang, Wenwu
language : en
Publisher: IGI Global
Release Date : 2010-07-31
Machine Audition Principles Algorithms And Systems written by Wang, Wenwu and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-31 with Computers categories.
Machine audition is the study of algorithms and systems for the automatic analysis and understanding of sound by machine. It has recently attracted increasing interest within several research communities, such as signal processing, machine learning, auditory modeling, perception and cognition, psychology, pattern recognition, and artificial intelligence. However, the developments made so far are fragmented within these disciplines, lacking connections and incurring potentially overlapping research activities in this subject area. Machine Audition: Principles, Algorithms and Systems contains advances in algorithmic developments, theoretical frameworks, and experimental research findings. This book is useful for professionals who want an improved understanding about how to design algorithms for performing automatic analysis of audio signals, construct a computing system for understanding sound, and learn how to build advanced human-computer interactive systems.