Evolutionary Image Analysis and Signal Processing

Stefano Cagnoni

ISBN 10: 3642101852 / ISBN 13: 9783642101854

Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2010

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - 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.

Codice articolo 9783642101854

Dati bibliografici

• Titolo: Evolutionary Image Analysis and Signal Processing
• Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 3642101852
• ISBN 13: 9783642101854
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 13 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 13 millimetri di profondità
• Peso: 341 grammi

Descrizione articolo

Riassunto

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.

Dalla quarta di copertina

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.