Evolutionary Image Analysis and Signal Processing

Herausgegeben:Cagnoni, Stefano

• Broschiertes Buch

Produktbeschreibung

The publication of this book on evolutionaryImage Analysis and Signal P- cessing (IASP) has two main goals. The ?rst, occasional one is to celebrate the 10th edition of EvoIASP, the workshop which has been the only event speci?cally dedicated to this topic since 1999. The second, more important one is to give an overview of the opportunities o?ered by Evolutionary C- putation (EC) techniques to computer vision,pattern recognition,and image and signal processing. It is not possible to celebrate EvoIASP properly without ?rst ackno- edging EvoNET, the EU-funded network of excellence, which has made it possible for Europe to build a strong European research community on EC. Thanks to the success of the ?rst, pioneering event organized by EvoNET, held in 1998 in Paris, it was possible to realize that not only was EC a f- tile ground for basic research but also there were several application ?elds to which EC techniques could o?er a valuable contribution. That was how the ideaofcreatingasingleevent,EvoWorkshops,outofacollectionofworkshops dedicated to applications of EC, was born. Amongst the possible application ?elds for EC, IASP was selected almost accidentally, due to the occasional presence, within EvoNET, of less than a handful of researchers who were interested in it. I would lie if I stated that the event was a great success since its very start, but it was successful enough to survive healthily for a couple of years, before reaching its present size, relevance, and popularity.

Produktdetails

• Studies in Computational Intelligence 213
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-642-10185-4
• Softcover reprint of hardcover 1st ed. 2009
• Seitenzahl: 220
• Erscheinungstermin: 28. Oktober 2010
• Englisch
• Abmessung: 235mm x 155mm x 13mm
• Gewicht: 337g
• ISBN-13: 9783642101854
• ISBN-10: 3642101852
• Artikelnr.: 33707527

Inhaltsangabe

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.