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Springer Advances in Reasoning-Based Image Processing Systems

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Description

Explore the latest developments in computational intelligence with Advances in Reasoning-Based Image Processing Intelligent Systems. Published by Springer as part of the Intelligent Systems Reference Library, volume 29 provides a deep look into both conventional and intelligent paradigms used in modern image analysis. This text covers essential topics for researchers and professionals in computer science and AI. It examines learning-based image representation, advanced video coding, and intelligent processing within medical vision systems. Readers can find detailed information on similarity learning models for image reconstruction and visual perception methods used for mobile robot motion control. By covering specialized areas such as shape-based invariant features extraction and paraconsistent neural networks, this book serves as a technical resource for understanding how human brain activity simulations and intelligent representation function within computational systems. It is a comprehensive guide for those studying the intersection of reasoning-based techniques and advanced image processing.

Key Features

Covers learning-based image representation and advanced video coding techniques for modern digital analysis.

Explores intelligent image processing and analysis specifically for medical vision systems.

Provides insights into similarity learning models used for high-quality image reconstruction.

Discusses visual perception applications for mobile robot motion control and simulation.

Includes technical studies on shape-based invariant features extraction and paraconsistent neural networks.

Examines creativity and intelligent representation within complex computational systems.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
13 January 2012
Listed Since
07 September 2011

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No barcode data available

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