Metaheuristics for Data Clustering and Image Segmentation

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, diffe...

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Detaylı Bibliyografya
Asıl Yazarlar: Ramadas, Meera (Yazar), Abraham, Ajith (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edisyon:1st ed. 2019.
Seri Bilgileri:Intelligent Systems Reference Library, 152
Konular:
Computational intelligence.
Artificial intelligence.
Computer vision.
Algorithms.
Computational Intelligence.
Artificial Intelligence.
Computer Vision.
Online Erişim:Full-text access
OPAC'ta görüntüle
Diğer Bilgiler
Özet: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.
Fiziksel Özellikler:IX, 163 p. 78 illus., 59 illus. in color. online resource.
ISBN:9783030040970
ISSN:1868-4408 ;
DOI:10.1007/978-3-030-04097-0

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