Evolutionary image analysis and signal processing

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, pa...

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Détails bibliographiques
Auteur principal: Kacprzyk, Janusz, 1947-
Autres auteurs: Cagnoni, Stefano (Directeur de la publication)
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Édition:1st ed. 2009.
Collection:Studies in Computational Intelligence 213
Accès en ligne:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Note: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Evolutionary Image Analysis and Signal Processing, Texte imprimé, 9783642016356
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505 1 |a 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 
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520 |a 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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