大葉大學圖書館 |

Hybrid soft computing for multilevel image and data segmentation[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.6
書名/作者:	Hybrid soft computing for multilevel image and data segmentation/ by Sourav De ... [et al.].
其他作者:	De, Sourav.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xiv, 235 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Image segmentation.
標題:	Soft computing.
標題:	Computer Science.
標題:	Artificial Intelligence (incl. Robotics)
標題:	Computational Intelligence.
標題:	Computer Imaging, Vision, Pattern Recognition and Graphics.
ISBN:	9783319475240
ISBN:	9783319475233
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-47524-0

Hybrid soft computing for multilevel image and data segmentation[electronic resource] /
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:

602455
Image segmentation.

LC Class. No.: TA1632

Dewey Class. No.: 006.6

Hybrid soft computing for multilevel image and data segmentation[electronic resource] /
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520 $a 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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