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Hybrid Metaheuristics for Image Analysis

2018-07-30 Computers
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Release : 2018-07-30
Genre : Computers
Kind : eBook
Book Rating : 258/5 ( reviews)

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Book Synopsis Hybrid Metaheuristics for Image Analysis by : Siddhartha Bhattacharyya

Download or read book Hybrid Metaheuristics for Image Analysis written by Siddhartha Bhattacharyya. This book was released on 2018-07-30. Available in PDF, EPUB and Kindle. Book excerpt: This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization. The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.

Applications of Hybrid Metaheuristic Algorithms for Image Processing

2020-03-27 Technology & Engineering
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Release : 2020-03-27
Genre : Technology & Engineering
Kind : eBook
Book Rating : 775/5 ( reviews)

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Book Synopsis Applications of Hybrid Metaheuristic Algorithms for Image Processing by : Diego Oliva

Download or read book Applications of Hybrid Metaheuristic Algorithms for Image Processing written by Diego Oliva. This book was released on 2020-03-27. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Hybrid Metaheuristics for Image Analysis

2019-08-21
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Release : 2019-08-21
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Kind : eBook
Book Rating : 974/5 ( reviews)

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Book Synopsis Hybrid Metaheuristics for Image Analysis by : Siddhartha Bhattacharyya

Download or read book Hybrid Metaheuristics for Image Analysis written by Siddhartha Bhattacharyya. This book was released on 2019-08-21. Available in PDF, EPUB and Kindle. Book excerpt: This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization. The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.

Recent Advances in Hybrid Metaheuristics for Data Clustering

2020-06-02 Computers
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Release : 2020-06-02
Genre : Computers
Kind : eBook
Book Rating : 609/5 ( reviews)

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Book Synopsis Recent Advances in Hybrid Metaheuristics for Data Clustering by : Sourav De

Download or read book Recent Advances in Hybrid Metaheuristics for Data Clustering written by Sourav De. This book was released on 2020-06-02. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics and their application to data clustering. Metaheuristics are designed to tackle complex clustering problems where classical clustering algorithms have failed to be either effective or efficient. The authors noted experts on the topic provide a text that can aid in the design and development of hybrid metaheuristics to be applied to data clustering. The book includes performance analysis of the hybrid metaheuristics in relationship to their conventional counterparts. In addition to providing a review of data clustering, the authors include in-depth analysis of different optimization algorithms. The text offers a step-by-step guide in the build-up of hybrid metaheuristics and to enhance comprehension. In addition, the book contains a range of real-life case studies and their applications. This important text: Includes performance analysis of the hybrid metaheuristics as related to their conventional counterparts Offers an in-depth analysis of a range of optimization algorithms Highlights a review of data clustering Contains a detailed overview of different standard metaheuristics in current use Presents a step-by-step guide to the build-up of hybrid metaheuristics Offers real-life case studies and applications Written for researchers, students and academics in computer science, mathematics, and engineering, Recent Advances in Hybrid Metaheuristics for Data Clustering provides a text that explores the current data clustering approaches using a range of computational intelligence techniques.

Metaheuristic Algorithms for Image Segmentation: Theory and Applications

2019-03-02 Technology & Engineering
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Release : 2019-03-02
Genre : Technology & Engineering
Kind : eBook
Book Rating : 314/5 ( reviews)

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Book Synopsis Metaheuristic Algorithms for Image Segmentation: Theory and Applications by : Diego Oliva

Download or read book Metaheuristic Algorithms for Image Segmentation: Theory and Applications written by Diego Oliva. This book was released on 2019-03-02. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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