£114.00

Springer Hybrid Metaheuristic Algorithms for Image Processing 890

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Description

Explore the latest advancements in computational intelligence with this specialized volume from Springer. This book provides a comprehensive collection of recent hybrid methods designed for image processing tasks. By combining evolutionary, swarm, machine learning, and deep learning approaches, the text offers a modern perspective on solving complex visual data problems. Readers will find detailed explorations into various domains, ranging from fundamental image segmentation to advanced object recognition through complex methodologies. The content also covers significant medical applications, making it a versatile resource for those studying how these tools function in real-world scenarios. This volume is an essential resource for academic growth. It is designed primarily for undergraduate and postgraduate students of science and engineering who need a solid understanding of the theory and practical applications of hybrid metaheuristic algorithms. Whether you are studying basic image processing or moving into deep learning, this book helps bridge the gap between theoretical methodology and practical implementation.

Key Features

Covers a wide range of hybrid methods including evolutionary, swarm, machine learning, and deep learning algorithms.

Explores diverse image processing areas such as segmentation and object recognition using complex approaches.

Includes specific discussions on medical applications to demonstrate real-world utility of these computational tools.

Provides a theoretical overview of methodologies to help readers understand the foundation of these applications.

Tailored for academic use, making it an ideal resource for undergraduate and postgraduate science students.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
28 March 2020
Listed Since
15 January 2020

Barcode

No barcode data available

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