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Hybrid soft computing for multilevel...
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Hybrid soft computing for multilevel image and data segmentation
Record Type:
Electronic resources : Monograph/item
Title/Author:
Hybrid soft computing for multilevel image and data segmentation/ by Sourav De ... [et al.].
other author:
De, Sourav.
Published:
Cham :Springer International Publishing : : 2016.,
Description:
xiv, 235 p. :ill., digital ;24 cm.
[NT 15003449]:
Introduction -- Image Segmentation: A Review -- Self-supervised Gray Level Image Segmentation Using an Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation Function -- Self-supervised Gray Level Image Segmentation Using Multiobjective Based Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Multiobjective Based Parallel Optimized MUSIG (ParaOptiMUSIG) Activation Function -- Unsupervised Genetic Algorithm Based Automatic Image Segmentation and Data Clustering Technique Validated by Fuzzy Intercluster Hostility Index.
Contained By:
Springer eBooks
Subject:
Image segmentation. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-47524-0
ISBN:
9783319475240
Hybrid soft computing for multilevel image and data segmentation
Hybrid soft computing for multilevel image and data segmentation
[electronic resource] /by Sourav De ... [et al.]. - Cham :Springer International Publishing :2016. - xiv, 235 p. :ill., digital ;24 cm. - Computational intelligence methods and applications,2510-1765. - Computational intelligence methods and applications..
Introduction -- Image Segmentation: A Review -- Self-supervised Gray Level Image Segmentation Using an Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation Function -- Self-supervised Gray Level Image Segmentation Using Multiobjective Based Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Multiobjective Based Parallel Optimized MUSIG (ParaOptiMUSIG) Activation Function -- Unsupervised Genetic Algorithm Based Automatic Image Segmentation and Data Clustering Technique Validated by Fuzzy Intercluster Hostility Index.
This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures. This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.
ISBN: 9783319475240
Standard No.: 10.1007/978-3-319-47524-0doiSubjects--Topical Terms:
2132796
Image segmentation.
LC Class. No.: TA1632
Dewey Class. No.: 006.6
Hybrid soft computing for multilevel image and data segmentation
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Introduction -- Image Segmentation: A Review -- Self-supervised Gray Level Image Segmentation Using an Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Parallel OptiMUSIG (ParaOptiMUSIG) Activation Function -- Self-supervised Gray Level Image Segmentation Using Multiobjective Based Optimized MUSIG (OptiMUSIG) Activation Function -- Self-supervised Color Image Segmentation Using Multiobjective Based Parallel Optimized MUSIG (ParaOptiMUSIG) Activation Function -- Unsupervised Genetic Algorithm Based Automatic Image Segmentation and Data Clustering Technique Validated by Fuzzy Intercluster Hostility Index.
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This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures. This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.
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Computer Science (Springer-11645)
based on 0 review(s)
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11.線上閱覽_V
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EB TA1632 .H992 2016
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