Metaheuristics for Data Clustering and Image Segmentation

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Éditeur :

Springer


Paru le : 2018-12-12

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Description

In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
Pages
163 pages
Collection
n.c
Parution
2018-12-12
Marque
Springer
EAN papier
9783030040963
EAN PDF
9783030040970

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
16
Taille du fichier
6789 Ko
Prix
94,94 €
EAN EPUB
9783030040970

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
16
Taille du fichier
16660 Ko
Prix
94,94 €

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