Evolutionary Image Analysis and Signal Processing [electronic resource] / edited by Stefano Cagnoni.

By: Cagnoni, Stefano [editor.]Contributor(s): SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Computational Intelligence: 213Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: XV, 204 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642016363Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Signal, Image and Speech Processing | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
Evolutionary Image Analysis and Signal Processing -- Texture Image Segmentation Using an Interactive Evolutionary Approach -- Detecting Scale-Invariant Regions Using Evolved Image Operators -- Online Evolvable Pattern Recognition Hardware -- A Variant Program Structure in Tree-Based Genetic Programming for Multiclass Object Classification -- Genetic Programming for Generative Learning and Recognition of Hand-Drawn Shapes -- Optimizing a Medical Image Analysis System Using Mixed-Integer Evolution Strategies -- Memetic Differential Evolution Frameworks in Filter Design for Defect Detection in Paper Production -- Fast Genetic Scan Matching in Mobile Robotics -- Distributed Differential Evolution for the Registration of Satellite and Multimodal Medical Imagery -- Euclidean Distance Fit of Conics Using Differential Evolution -- An Evolutionary FIR Filter Design Method.
In: Springer eBooksSummary: This book on Evolutionary Image Analysis and Signal Processing, besides celebrating ten years of EvoIASP, the only event specifically dedicated to this topic since 1999, offers readers a panoramic view of what can be presently achieved using Evolutionary Computation techniques in computer vision, pattern recognition, and image and signal processing. Its chapters mostly consist of extended versions of a selection of papers which were presented at recent editions of EvoIASP. The book includes examples which span, rather uniformly, the whole range of roles Evolutionary Computation techniques may have in such applications, from representing optimization tools used to tune or refine parameters or components of a mostly predefined solution up to situations where the solution itself is intrinsically evolutionary.
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Evolutionary Image Analysis and Signal Processing -- Texture Image Segmentation Using an Interactive Evolutionary Approach -- Detecting Scale-Invariant Regions Using Evolved Image Operators -- Online Evolvable Pattern Recognition Hardware -- A Variant Program Structure in Tree-Based Genetic Programming for Multiclass Object Classification -- Genetic Programming for Generative Learning and Recognition of Hand-Drawn Shapes -- Optimizing a Medical Image Analysis System Using Mixed-Integer Evolution Strategies -- Memetic Differential Evolution Frameworks in Filter Design for Defect Detection in Paper Production -- Fast Genetic Scan Matching in Mobile Robotics -- Distributed Differential Evolution for the Registration of Satellite and Multimodal Medical Imagery -- Euclidean Distance Fit of Conics Using Differential Evolution -- An Evolutionary FIR Filter Design Method.

This book on Evolutionary Image Analysis and Signal Processing, besides celebrating ten years of EvoIASP, the only event specifically dedicated to this topic since 1999, offers readers a panoramic view of what can be presently achieved using Evolutionary Computation techniques in computer vision, pattern recognition, and image and signal processing. Its chapters mostly consist of extended versions of a selection of papers which were presented at recent editions of EvoIASP. The book includes examples which span, rather uniformly, the whole range of roles Evolutionary Computation techniques may have in such applications, from representing optimization tools used to tune or refine parameters or components of a mostly predefined solution up to situations where the solution itself is intrinsically evolutionary.

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