£120.05

Springer Hybrid Metaheuristic Algorithms for Image Processing 890

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Description

Explore the latest advancements in computational intelligence with this comprehensive volume from Springer. This book provides a deep look into recent hybrid methods designed specifically for image processing tasks. By combining various approaches, the text covers evolutionary, swarm, machine learning, and deep learning algorithms to solve complex visual problems. Readers will find detailed explorations of different image processing domains, ranging from fundamental image segmentation to advanced object recognition. The content also covers practical medical applications, making it a versatile resource for various scientific fields. The book balances theoretical methodologies with practical applications, offering a clear overview of how these tools function in real-world scenarios. This publication serves as an essential resource for those studying the intersection of artificial intelligence and computer vision. It is designed to support the learning needs of undergraduate and postgraduate students in science and engineering, providing the technical foundation required to understand and implement modern hybrid metaheuristic algorithms.

Key Features

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

Explores diverse applications such as image segmentation and complex object recognition techniques.

Includes specialized content on medical applications of image processing technologies.

Provides a thorough discussion of the underlying theory for the methodologies used in these computational tools.

Designed as a primary resource for undergraduate and postgraduate students in science and engineering fields.

Part of the Studies in Computational Intelligence series, volume 890, ensuring academic rigor.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
28 March 2021
Listed Since
20 March 2021

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