Applications of Hybrid Metaheuristic Algorithms for Image Processing
Language: English
Published by Palgrave Macmillan, 2020
Series: Book 396 of 538 - Studies in Computational Intelligence
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 169.70
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.
Seller Inventory # 9783030409760
- Title
- Applications of Hybrid Metaheuristic Algorithms for Image Processing
- Author
- Salvador Hinojosa
- Publisher
- Palgrave Macmillan
- Publication year
- 2020
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3030409767
- ISBN 13
- 9783030409760
- Item weight
- 864 grams
- Dimensions
- 241x160x33 mm
- Series
- Book 396 of 538: Studies in Computational Intelligence
This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing.
The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing.
The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.
"About the title" may belong to another edition of this title.
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