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Titlebook: Evolutionary Image Analysis and Signal Processing; Stefano Cagnoni Book 2009 Springer-Verlag Berlin Heidelberg 2009 Signal.calculus.cognit

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书目名称Evolutionary Image Analysis and Signal Processing
编辑Stefano Cagnoni
视频video
概述Presents recent developments of Evolutionary Image Analysis and Signal Processing.Extended contributions from EvoIASP 2007 and more
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Evolutionary Image Analysis and Signal Processing;  Stefano Cagnoni Book 2009 Springer-Verlag Berlin Heidelberg 2009 Signal.calculus.cognit
描述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
出版日期Book 2009
关键词Signal; calculus; cognition; computer vision; evolution; evolutionary computation; genetic programming; ima
版次1
doihttps://doi.org/10.1007/978-3-642-01636-3
isbn_softcover978-3-642-10185-4
isbn_ebook978-3-642-01636-3Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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Harmonic Analysis of Databases and Matricesntal results related to the convergence, accuracy and speed of the proposed algorithm with different coding approaches are reported. We compare our approach with other scan matching algorithms proposed in the literature, and we show that our approach is faster and more accurate than the others.
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Jason Bello∗,Yiran Li,Robert S. Strichartz† solved using a cubic equation.We also show how to combine DE with a conventional deterministic algorithm to initialize it. We present experiments that show better results than those previously reported. In addition, our solutions have a very low variance, which indicates the robustness of the approach.
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Optimizing a Medical Image Analysis System Using Mixed-Integer Evolution Strategiesan deal with nonlinear functions and different types of parameters, including integer, nominal discrete and continuous variables. MIES turns out to be well suited for this task. The results presented in this contribution will summarize and extend recent studies on benchmark functions and the IVUS image analysis optimization problem.
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