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Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization, Abidi Mongi A., Gribok Andrei V., Paik Joonki


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Автор: Abidi Mongi A., Gribok Andrei V., Paik Joonki
Название:  Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization
ISBN: 9783319835013
Издательство: Springer
Классификация:



ISBN-10: 3319835017
Обложка/Формат: Paperback
Страницы: 293
Вес: 0.44 кг.
Дата издания: 04.07.2018
Серия: Advances in computer vision and pattern recognition
Язык: English
Издание: Softcover reprint of
Иллюстрации: 2 tables, color; 23 illustrations, color; 104 illustrations, black and white; xv, 293 p. 127 illus., 23 illus. in color.
Размер: 23.39 x 15.60 x 1.65 cm
Читательская аудитория: General (us: trade)
Подзаголовок: Ill-posed problems and regularization
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems.


Optimization Techniques in Computer Vision

Автор: Mongi A. Abidi; Andrei V. Gribok; Joonki Paik
Название: Optimization Techniques in Computer Vision
ISBN: 3319463632 ISBN-13(EAN): 9783319463636
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems. Unconstrained optimization gives the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained optimization problems have been intensively studied, and many algorithms and tools have been developed to solve them. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc.

Optimization plays a major role in a wide variety of theories for image processing and computer vision. Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision.
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

Автор: Andrea Lodi; Michela Milano; Paolo Toth
Название: Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
ISBN: 3642135196 ISBN-13(EAN): 9783642135194
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Constitutes the refereed proceedings of the 7th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2010, held in Bologna, Italy, in June 2010.

Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

Автор: Willem-Jan van Hoeve; Elvin Coban
Название: Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
ISBN: 3642019285 ISBN-13(EAN): 9783642019289
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Constitutes the refereed proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2009, held in Pittsburgh, PA, USA, in May 2009.


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