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Metaheuristic Algorithms for Image Segmentation: Theory and Applications, Diego Oliva; Mohamed Abd Elaziz; Salvador Hinojosa


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Автор: Diego Oliva; Mohamed Abd Elaziz; Salvador Hinojosa
Название:  Metaheuristic Algorithms for Image Segmentation: Theory and Applications
ISBN: 9783030129309
Издательство: Springer
Классификация:


ISBN-10: 3030129306
Обложка/Формат: Hardcover
Страницы: 226
Вес: 0.54 кг.
Дата издания: 2019
Серия: Studies in Computational Intelligence
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 43 illustrations, color; 15 illustrations, black and white; xv, 226 p. 58 illus., 43 illus. in color.
Размер: 234 x 156 x 14
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:
This book presents a study of the most important methods of image segmentation and how they are extended and improved using metaheuristic algorithms. The segmentation approaches selected have been extensively applied to the task of segmentation (especially in thresholding), and have also been implemented using various metaheuristics and hybridization techniques leading to a broader understanding of how image segmentation problems can be solved from an optimization perspective. The field of image processing is constantly changing due to the extensive integration of cameras in devices; for example, smart phones and cars now have embedded cameras. The images have to be accurately analyzed, and crucial pre-processing steps, like image segmentation, and artificial intelligence, including metaheuristics, are applied in the automatic analysis of digital images. Metaheuristic algorithms have also been used in various fields of science and technology as the demand for new methods designed to solve complex optimization problems increases.
This didactic book is primarily intended for undergraduate and postgraduate students of science, engineering, and computational mathematics. It is also suitable for courses such as artificial intelligence, advanced image processing, and computational intelligence. The material is also useful for researches in the fields of evolutionary computation, artificial intelligence, and image processing.

Дополнительное описание: Introduction.- Optimization.- Metaheuristic optimization.- Image processing.- Image Segmentation using metaheuristics.- Multilevel thresholding for image segmentation based on metaheuristic Algorithms.- Otsu’s between class variance and the tree seed algo


A Metaheuristic Approach to Protein Structure Prediction

Автор: Nanda Dulal Jana; Swagatam Das; Jaya Sil
Название: A Metaheuristic Approach to Protein Structure Prediction
ISBN: 3030090752 ISBN-13(EAN): 9783030090753
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book introduces characteristic features of the protein structure prediction (PSP) problem. It focuses on systematic selection and improvement of the most appropriate metaheuristic algorithm to solve the problem based on a fitness landscape analysis, rather than on the nature of the problem, which was the focus of methodologies in the past. Protein structure prediction is concerned with the question of how to determine the three-dimensional structure of a protein from its primary sequence. Recently a number of successful metaheuristic algorithms have been developed to determine the native structure, which plays an important role in medicine, drug design, and disease prediction. This interdisciplinary book consolidates the concepts most relevant to protein structure prediction (PSP) through global non-convex optimization. It is intended for graduate students from fields such as computer science, engineering, bioinformatics and as a reference for researchers and practitioners.

Metaheuristics for Data Clustering and Image Segmentation

Автор: Meera Ramadas; Ajith Abraham
Название: Metaheuristics for Data Clustering and Image Segmentation
ISBN: 3030040968 ISBN-13(EAN): 9783030040963
Издательство: Springer
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Цена: 93160.00 T
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Описание: In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.

Metaheuristic Applications to Speech Enhancement

Автор: Prajna Kunche; K.V.V.S. Reddy
Название: Metaheuristic Applications to Speech Enhancement
ISBN: 3319316818 ISBN-13(EAN): 9783319316819
Издательство: Springer
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Цена: 60940.00 T
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Описание: Readers willbe able to understand the fundamentals of speech processing as well as theoptimization techniques, how the speech enhancement algorithms are implementedby utilizing optimization methods, and will be given the tools to develop newalgorithms.

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Автор: Dash Sujata, Tripathy B. K., Rahman Atta Ur
Название: Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms
ISBN: 1522528571 ISBN-13(EAN): 9781522528579
Издательство: Mare Nostrum (Eurospan)
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Цена: 257790.00 T
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Описание: The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems.The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.

Optimization of Process Flowsheets through Metaheuristic Techniques

Автор: Ponce-Ortega
Название: Optimization of Process Flowsheets through Metaheuristic Techniques
ISBN: 3319917218 ISBN-13(EAN): 9783319917214
Издательство: Springer
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Цена: 60550.00 T
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Описание: This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques.

A Metaheuristic Approach to Protein Structure Prediction

Автор: Jana
Название: A Metaheuristic Approach to Protein Structure Prediction
ISBN: 3319747746 ISBN-13(EAN): 9783319747743
Издательство: Springer
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Цена: 93160.00 T
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Описание: Metaheuristic Protein Structure Prediction-An Overview.- Related Works.- Continuous Landscape Analysis using Random Walk Algorithm.- Landscape Characterization and Algorithms Selection for the PSP Problem.- The Levy distributed Parameter Adaptive Metaheuristic Algorithm for Protein Structure Prediction.- Protein Structure Prediction using Improved Variants of Metaheuristic Algorithms.- Hybrid Metaheuristic Approach for Protein Structure Prediction.- Conclusions and Future Research.


Metaheuristic Computation with MATLAB®

Автор: Cuevas, Erik , Rodriguez, Alma
Название: Metaheuristic Computation with MATLAB®
ISBN: 0367438860 ISBN-13(EAN): 9780367438869
Издательство: Taylor&Francis
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Цена: 122490.00 T
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Описание: The main purpose of this book is to provide a unified view of the most popular metaheuristic methods. Under this perspective, it has presented the fundamental design principles as well as the operators of metaheuristic approaches which are considered essential.

Optimization of Process Flowsheets through Metaheuristic Techniques

Автор: Jos? Mar?a Ponce-Ortega; Luis Germ?n Hern?ndez-P?r
Название: Optimization of Process Flowsheets through Metaheuristic Techniques
ISBN: 3030062848 ISBN-13(EAN): 9783030062842
Издательство: Springer
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Цена: 60550.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus®, HYSIS®, Super Pro Designer® linked to a variety of metaheuristic techniques implemented in Matlab®, Excel®, C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab® routines are included as electronic supporting material.

Metaheuristic Clustering

Автор: Swagatam Das; Ajith Abraham; Amit Konar
Название: Metaheuristic Clustering
ISBN: 3642100716 ISBN-13(EAN): 9783642100710
Издательство: Springer
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Цена: 139750.00 T
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Описание: Cluster analysis means the organization of an unlabeled collection of objects into separate groups based on their similarity. With the use of several real world examples, this book formulates clustering as an optimization problem.

Advances in Metaheuristics Algorithms: Methods and Applications

Автор: Cuevas
Название: Advances in Metaheuristics Algorithms: Methods and Applications
ISBN: 3319893084 ISBN-13(EAN): 9783319893082
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems.

Advances in Metaheuristics Algorithms: Methods and Applications

Автор: Erik Cuevas; Daniel Zald?var; Marco P?rez-Cisneros
Название: Advances in Metaheuristics Algorithms: Methods and Applications
ISBN: 3030077365 ISBN-13(EAN): 9783030077365
Издательство: Springer
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Цена: 93160.00 T
Наличие на складе: Поставка под заказ.
Описание:

This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.

Handbook of Metaheuristics

Автор: Gendreau
Название: Handbook of Metaheuristics
ISBN: 1441916636 ISBN-13(EAN): 9781441916631
Издательство: Springer
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Цена: 222670.00 T
Наличие на складе: Поставка под заказ.
Описание: Metaheuristics have grown into one of the most prominent areas of operations research. This update of a trailblazing volume examines the latest developments in the field.


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