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Springer Hybrid Metaheuristic Algorithms for Image Processing

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Description

Explore the latest developments in image processing with this Springer publication from the Studies in Computational Intelligence series. This book provides a comprehensive collection of recent hybrid methods, integrating evolutionary, swarm, machine learning, and deep learning algorithms. Readers will find detailed explorations of various image processing areas, ranging from segmentation techniques to object recognition using complex approaches and medical applications. By discussing the underlying theory of these methodologies, the text offers a clear overview of how these tools are applied in real-world scenarios. This volume serves as an essential resource for undergraduate and postgraduate students studying science, engineering, and computer science.

Key Features

This Springer book covers recent hybrid methods including evolutionary, swarm, machine learning, and deep learning algorithms.

The text explores diverse image processing areas such as image segmentation and object recognition.

Chapters include specific discussions on medical applications and complex approaches to image processing.

The content provides a theoretical overview of the methodologies used in various image processing tools.

This volume is designed for undergraduate and postgraduate students in science, engineering, and computer science.

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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