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- Category: Mathematics
- Author: Stefano Cagnoni, Evelyne Lutton, and Gustavo Olague
- Pages: 466 pages
Read and download free eBook intituled Genetic and Evolutionary Computation for Image Processing and Analysis in format – 466 pages created by Stefano Cagnoni, Evelyne Lutton, and Gustavo Olague.
Image analysis and processing is steadily gaining relevance within the large number of application fields to which genetic and evolutionary computation (GEC) techniques are applied. Although more and more examples of such applications can be found in literature, they are scattered, apart from a few exceptions, in proceedings and journals dedicated to more general topics. This book is the first attempt to offer a panoramic view on the field, by describing applications of most mainstream GEC techniques to a wide range of problems in image processing and analysis. More than 20 leading researchers in the field have contributed to this book, covering topics ranging from low-level image processing to high-level image analysis in advanced computer vision applications. Although the book is mainly application-oriented, particular care has been given to introducing GEC methods, in each chapter, at a level which makes them accessible to a wide audience.
The expected target of the book comprises practitioners and researchers in image analysis and processing who may not be familiar with GEC techniques. At the same time, the book can as well be of interest for researchers in evolutionary computation, since most contributions focus on applications of genetic and evolutionary techniques which are based on nontrivial implementations of such methods. This feature reflects the nature of the contributions which are authored both by researchers for which GEC is the main field of interest and by researchers whose work is mainly focused on image processing and analysis.
Stefano Cagnoni graduated in Electronic Engineering at the University of Florence in 1988 where he has been a PhD student and a post-doc until 1997, working in the Bioengineering Lab of the Dept. of Electronic Engineering. He received the PhD degree in Bioengineering in 1993.
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Genetic and Evolutionary Computation for Image Processing and Analysis
