Modern Algorithms for Image Processing, Vladimir Kovalevsky
Автор: Cormen, Thomas H., E Название: Introduction to algorithms 3 ed. ISBN: 0262033844 ISBN-13(EAN): 9780262033848 Издательство: MIT Press Рейтинг: Цена: 183920.00 T Наличие на складе: Нет в наличии. Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.
Автор: Agarwal, Dr Basant, Baka, Benjamin Название: Hands-On Data Structures and Algorithms with Python 2 ed ISBN: 1788995570 ISBN-13(EAN): 9781788995573 Издательство: Неизвестно Рейтинг: Цена: 53940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data structures help us to organize and align the data in a very efficient way. This book will surely help you to learn important and essential data structures through Python implementation for better understanding of the concepts.
Автор: Damir Gainanov Название: Graphs for Pattern Recognition: Infeasible Systems of Linear Inequalities ISBN: 3110480131 ISBN-13(EAN): 9783110480139 Издательство: Walter de Gruyter Рейтинг: Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This monograph deals with mathematical constructions that are foundational in such an important area of data mining as pattern recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities, whose generalized solutions act as building blocks of geometric decision rules for pattern recognition.Infeasible systems of linear inequalities prove to be a key object in pattern recognition problems described in geometric terms thanks to the committee method. Such infeasible systems of inequalities represent an important special subclass of infeasible systems of constraints with a monotonicity property - systems whose multi-indices of feasible subsystems form abstract simplicial complexes (independence systems), which are fundamental objects of combinatorial topology.The methods of data mining and machine learning discussed in this monograph form the foundation of technologies like big data and deep learning, which play a growing role in many areas of human-technology interaction and help to find solutions, better solutions and excellent solutions. Contents: PrefacePattern recognition, infeasible systems of linear inequalities, and graphsInfeasible monotone systems of constraintsComplexes, (hyper)graphs, and inequality systemsPolytopes, positive bases, and inequality systemsMonotone Boolean functions, complexes, graphs, and inequality systemsInequality systems, committees, (hyper)graphs, and alternative coversBibliographyList of notationIndex
Автор: Parker J J Название: Algorithms for Image Processing and Computer Vision ISBN: 0470643854 ISBN-13(EAN): 9780470643853 Издательство: Wiley Рейтинг: Цена: 83430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Programmers, scientists, and engineers are always in need of newer techniques and algorithms to manipulate and interpret images. Algorithms for Image Processing and Computer Vision is an accessible collection of algorithms for common image processing applications that simplifies complicated mathematical calculations.
Автор: Ilia V. Safonov; Ilya V. Kurilin; Michael N. Rycha Название: Adaptive Image Processing Algorithms for Printing ISBN: 9811069301 ISBN-13(EAN): 9789811069307 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents essential algorithms for the image processing pipeline of photo-printers and accompanying software tools, offering an exposition of multiple image enhancement algorithms, smart aspect-ratio changing techniques for borderless printing and approaches for non-standard printing modes. All the techniques described are content-adaptive and operate in an automatic mode thanks to machine learning reasoning or ingenious heuristics. The first part includes algorithms, for example, red-eye correction and compression artefacts reduction, that can be applied in any photo processing application, while the second part focuses specifically on printing devices, e.g. eco-friendly and anaglyph printing. The majority of the techniques presented have a low computational complexity because they were initially designed for integration in system-on-chip. The book reflects the authors’ practical experience in algorithm development for industrial R&D.
Автор: Barfoot Timothy D Название: State Estimation for Robotics ISBN: 1107159393 ISBN-13(EAN): 9781107159396 Издательство: Cambridge Academ Рейтинг: Цена: 95030.00 T Наличие на складе: Невозможна поставка. Описание: This book is intended for students and practitioners of robotics who are interested in using noisy sensor data to estimate the position, orientation, and other state variables of robots as they move through the three-dimensional world. It covers classical and modern techniques commonly used in robotics today.
Автор: T. Pavlidis Название: Algorithms for Graphics and Image Processing ISBN: 364293210X ISBN-13(EAN): 9783642932106 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The technological developments of the last ten years have made com- puter graphics and image processing by computer popular. Graphic displays are of concern to anyone involved in image processing or pic- torial pattern recognition and many problems in graphics require methodologies from image processing for their solutions.
Автор: Steven Bell, Jing Pu, James Hegarty, Mark Horowitz Название: Compiling Algorithms for Heterogeneous Systems ISBN: 1681732637 ISBN-13(EAN): 9781681732633 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 72070.00 T Наличие на складе: Невозможна поставка. Описание: Most emerging applications in imaging and machine learning must perform immense amounts of computation while holding to strict limits on energy and power. To meet these goals, architects are building increasingly specialized compute engines tailored for these specific tasks. The resulting computer systems are heterogeneous, containing multiple processing cores with wildly different execution models. Unfortunately, the cost of producing this specialized hardware—and the software to control it—is astronomical. Moreover, the task of porting algorithms to these heterogeneous machines typically requires that the algorithm be partitioned across the machine and rewritten for each specific architecture, which is time consuming and prone to error.Over the last several years, the authors have approached this problem using domain-specific languages (DSLs): high-level programming languages customized for specific domains, such as database manipulation, machine learning, or image processing. By giving up generality, these languages are able to provide high-level abstractions to the developer while producing high performance output. The purpose of this book is to spur the adoption and the creation of domain-specific languages, especially for the task of creating hardware designs.In the first chapter, a short historical journey explains the forces driving computer architecture today. Chapter 2 describes the various methods for producing designs for accelerators, outlining the push for more abstraction and the tools that enable designers to work at a higher conceptual level. From there, Chapter 3 provides a brief introduction to image processing algorithms and hardware design patterns for implementing them. Chapters 4 and 5 describe and compare Darkroom and Halide, two domain-specific languages created for image processing that produce high-performance designs for both FPGAs and CPUs from the same source code, enabling rapid design cycles and quick porting of algorithms. The final section describes how the DSL approach also simplifies the problem of interfacing between application code and the accelerator by generating the driver stack in addition to the accelerator configuration.This book should serve as a useful introduction to domain-specialized computing for computer architecture students and as a primer on domain-specific languages and image processing hardware for those with more experience in the field.
Автор: Ilia V. Safonov; Ilya V. Kurilin; Michael N. Rycha Название: Adaptive Image Processing Algorithms for Printing ISBN: 9811349711 ISBN-13(EAN): 9789811349713 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents essential algorithms for the image processing pipeline of photo-printers and accompanying software tools, offering an exposition of multiple image enhancement algorithms, smart aspect-ratio changing techniques for borderless printing and approaches for non-standard printing modes. All the techniques described are content-adaptive and operate in an automatic mode thanks to machine learning reasoning or ingenious heuristics. The first part includes algorithms, for example, red-eye correction and compression artefacts reduction, that can be applied in any photo processing application, while the second part focuses specifically on printing devices, e.g. eco-friendly and anaglyph printing. The majority of the techniques presented have a low computational complexity because they were initially designed for integration in system-on-chip. The book reflects the authors’ practical experience in algorithm development for industrial R&D.
Автор: Steven Bell, Jing Pu, James Hegarty, Mark Horowitz Название: Compiling Algorithms for Heterogeneous Systems ISBN: 162705961X ISBN-13(EAN): 9781627059619 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 51750.00 T Наличие на складе: Невозможна поставка. Описание: Most emerging applications in imaging and machine learning must perform immense amounts of computation while holding to strict limits on energy and power. To meet these goals, architects are building increasingly specialized compute engines tailored for these specific tasks. The resulting computer systems are heterogeneous, containing multiple processing cores with wildly different execution models. Unfortunately, the cost of producing this specialized hardware—and the software to control it—is astronomical. Moreover, the task of porting algorithms to these heterogeneous machines typically requires that the algorithm be partitioned across the machine and rewritten for each specific architecture, which is time consuming and prone to error.Over the last several years, the authors have approached this problem using domain-specific languages (DSLs): high-level programming languages customized for specific domains, such as database manipulation, machine learning, or image processing. By giving up generality, these languages are able to provide high-level abstractions to the developer while producing high performance output. The purpose of this book is to spur the adoption and the creation of domain-specific languages, especially for the task of creating hardware designs.In the first chapter, a short historical journey explains the forces driving computer architecture today. Chapter 2 describes the various methods for producing designs for accelerators, outlining the push for more abstraction and the tools that enable designers to work at a higher conceptual level. From there, Chapter 3 provides a brief introduction to image processing algorithms and hardware design patterns for implementing them. Chapters 4 and 5 describe and compare Darkroom and Halide, two domain-specific languages created for image processing that produce high-performance designs for both FPGAs and CPUs from the same source code, enabling rapid design cycles and quick porting of algorithms. The final section describes how the DSL approach also simplifies the problem of interfacing between application code and the accelerator by generating the driver stack in addition to the accelerator configuration.This book should serve as a useful introduction to domain-specialized computing for computer architecture students and as a primer on domain-specific languages and image processing hardware for those with more experience in the field.
Автор: Hayes, Monson H. Название: Statistical digital signal processing and modeling ISBN: 0471594318 ISBN-13(EAN): 9780471594314 Издательство: Wiley Рейтинг: Цена: 304240.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book responds to the dramatic growth in digital signal processing (DSP) over the past decade. While its focal point is signal modeling, the book integrates and explores the relationships of signal modeling to the important problems of optimal filtering, spectral estimation, and adaptive filtering.
This book explores image processing from several perspectives: the creative, the theoretical (mainly mathematical), and the programmatical. It explains the basic principles of image processing, drawing on key concepts and techniques from mathematics, psychology of perception, computer science, and art, and introduces computer programming as a way to get more control over image processing operations. It does so without requiring college-level mathematics or prior programming experience. The content is supported by PixelMath, a freely available software program that helps the reader understand images as both visual and mathematical objects.
The first part of the book covers such topics as digital image representation, sampling, brightness and contrast, color models, geometric transformations, synthesizing images, stereograms, photomosaics, and fractals. The second part of the book introduces computer programming using an open-source version of the easy-to-learn Python language. It covers the basics of image analysis and pattern recognition, including edge detection, convolution, thresholding, contour representation, and K-nearest-neighbor classification. A chapter on computational photography explores such subjects as high-dynamic-range imaging, autofocusing, and methods for automatically inpainting to fill gaps or remove unwanted objects in a scene. Applications described include the design and implementation of an image-based game. The PixelMath software provides a "transparent" view of digital images by allowing the user to view the RGB values of pixels by zooming in on an image. PixelMath provides three interfaces: the pixel calculator; the formula page, an advanced extension of the calculator; and the Python window.
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