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Hybrid Soft Computing for Image Segmentation, Bhattacharyya Siddhartha, Dutta Paramartha, de Sourav


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Автор: Bhattacharyya Siddhartha, Dutta Paramartha, de Sourav
Название:  Hybrid Soft Computing for Image Segmentation
ISBN: 9783319836843
Издательство: Springer
Классификация:

ISBN-10: 3319836846
Обложка/Формат: Paperback
Страницы: 321
Вес: 0.48 кг.
Дата издания: 29.06.2018
Язык: English
Издание: Softcover reprint of
Иллюстрации: 89 tables, color; 87 illustrations, color; 75 illustrations, black and white; xvi, 321 p. 162 illus., 87 illus. in color.
Размер: 23.39 x 15.60 x 1.80 cm
Читательская аудитория: General (us: trade)
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems.


Hybrid Soft Computing for Image Segmentation

Автор: Siddhartha Bhattacharyya; Paramartha Dutta; Sourav
Название: Hybrid Soft Computing for Image Segmentation
ISBN: 3319472224 ISBN-13(EAN): 9783319472225
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization.The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.

Hybrid Soft Computing for Multilevel Image and Data Segmentation

Автор: de Sourav, Bhattacharyya Siddhartha, Chakraborty Susanta
Название: Hybrid Soft Computing for Multilevel Image and Data Segmentation
ISBN: 3319837583 ISBN-13(EAN): 9783319837581
Издательство: Springer
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Цена: 13974.00 р.
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Hybrid Soft Computing for Multilevel Image and Data Segmentation

Автор: Sourav De; Siddhartha Bhattacharyya; Susanta Chakr
Название: Hybrid Soft Computing for Multilevel Image and Data Segmentation
ISBN: 3319475231 ISBN-13(EAN): 9783319475233
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures.This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.

Phoneme-Based Speech Segmentation using Hybrid Soft Computing Framework

Автор: Mousmita Sarma; Kandarpa Kumar Sarma
Название: Phoneme-Based Speech Segmentation using Hybrid Soft Computing Framework
ISBN: 8132218612 ISBN-13(EAN): 9788132218616
Издательство: Springer
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Цена: 18284.00 р.
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Описание: The book discusses intelligent system design using soft computing and similar systems and their interdisciplinary applications. It also focuses on the recent trends to use soft computing as a versatile tool for designing a host of decision support systems.

Phoneme-Based Speech Segmentation using Hybrid Soft Computing Framework

Автор: Mousmita Sarma; Kandarpa Kumar Sarma
Название: Phoneme-Based Speech Segmentation using Hybrid Soft Computing Framework
ISBN: 8132235150 ISBN-13(EAN): 9788132235156
Издательство: Springer
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Цена: 15672.00 р.
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Описание: The book discusses intelligent system design using soft computing and similar systems and their interdisciplinary applications. It also focuses on the recent trends to use soft computing as a versatile tool for designing a host of decision support systems.

Deformable Meshes for Medical Image Segmentation

Автор: Dagmar Kainmueller
Название: Deformable Meshes for Medical Image Segmentation
ISBN: 3658070145 ISBN-13(EAN): 9783658070144
Издательство: Springer
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Цена: 9141.00 р.
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Описание: ГЇВїВЅ Segmentation of anatomical structures in medical image data is an essential task in clinical practice. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatomical structures, together with thorough evaluations of segmentation accuracy on clinical image data.

Genetic Learning for Adaptive Image Segmentation

Автор: Bir Bhanu; Sungkee Lee
Название: Genetic Learning for Adaptive Image Segmentation
ISBN: 0792394917 ISBN-13(EAN): 9780792394914
Издательство: Springer
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Цена: 27944.00 р.
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Описание: Genetic Learning for Adaptive Image Segmentation presents the first closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year, weather, etc.

Text Segmentation and Recognition for Enhanced Image Spam Detection: An Integrated Approach

Автор: Rajalingam Mallikka
Название: Text Segmentation and Recognition for Enhanced Image Spam Detection: An Integrated Approach
ISBN: 3030530469 ISBN-13(EAN): 9783030530464
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book discusses email spam detection and its challenges such as text classification and categorization.

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: 13974.00 р.
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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.

Genetic Learning for Adaptive Image Segmentation

Автор: Bir Bhanu; Sungkee Lee
Название: Genetic Learning for Adaptive Image Segmentation
ISBN: 1461361982 ISBN-13(EAN): 9781461361985
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Genetic Learning for Adaptive Image Segmentation presents the first closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year, weather, etc.

Metaheuristic Algorithms for Image Segmentation: Theory and Applications

Автор: Oliva Diego, Abd Elaziz Mohamed, Hinojosa Salvador
Название: Metaheuristic Algorithms for Image Segmentation: Theory and Applications
ISBN: 3030129330 ISBN-13(EAN): 9783030129330
Издательство: Springer
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Цена: 13974.00 р.
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Описание: 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.

Markov Random Fields in Image Segmentation

Автор: Kato Zoltan
Название: Markov Random Fields in Image Segmentation
ISBN: 1601985886 ISBN-13(EAN): 9781601985880
Издательство: Неизвестно
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Цена: 13656.00 р.
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Описание: Markov Random Fields in Image Segmentation introduces the fundamentals of Markovian modeling in image segmentation as well as providing a brief overview of recent advances in the field.


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