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Harmony search-based fuzzy clustering algorithms for image segmentation.

Algoritma-algoritma pengkelompokan kabur, yang tergolong di dalam kategori pembelajaran mesin tanpa selia, adalah di antara kaedah segmentasi imej yang paling berjaya. Namun demikian, terdapat dua isu utama yang membataskan keberkesanan kaedah ini: kepekaan terhadap pemilihan pusat kelompok permulaa...

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Main Author: Alia, Osama Moh’d Radi
Format: Thesis
Language:English
Published: 2011
Subjects:
QA75.5-76.95 Electronic computers. Computer science
Online Access:http://eprints.usm.my/42978/1/Pages_from_HARMONY_SEARCH-BASED_FUZZY.pdf
http://eprints.usm.my/42978/
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spelling my.usm.eprints.42978 http://eprints.usm.my/42978/ Harmony search-based fuzzy clustering algorithms for image segmentation. Alia, Osama Moh’d Radi QA75.5-76.95 Electronic computers. Computer science Algoritma-algoritma pengkelompokan kabur, yang tergolong di dalam kategori pembelajaran mesin tanpa selia, adalah di antara kaedah segmentasi imej yang paling berjaya. Namun demikian, terdapat dua isu utama yang membataskan keberkesanan kaedah ini: kepekaan terhadap pemilihan pusat kelompok permulaan dan ketidakpastian terhadap bilangan kelompok sebenar di dalam set data. Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. 2011-02 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/42978/1/Pages_from_HARMONY_SEARCH-BASED_FUZZY.pdf Alia, Osama Moh’d Radi (2011) Harmony search-based fuzzy clustering algorithms for image segmentation. PhD thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic QA75.5-76.95 Electronic computers. Computer science
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Alia, Osama Moh’d Radi
Harmony search-based fuzzy clustering algorithms for image segmentation.
description Algoritma-algoritma pengkelompokan kabur, yang tergolong di dalam kategori pembelajaran mesin tanpa selia, adalah di antara kaedah segmentasi imej yang paling berjaya. Namun demikian, terdapat dua isu utama yang membataskan keberkesanan kaedah ini: kepekaan terhadap pemilihan pusat kelompok permulaan dan ketidakpastian terhadap bilangan kelompok sebenar di dalam set data. Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset.
format Thesis
author Alia, Osama Moh’d Radi
author_facet Alia, Osama Moh’d Radi
author_sort Alia, Osama Moh’d Radi
title Harmony search-based fuzzy clustering algorithms for image segmentation.
title_short Harmony search-based fuzzy clustering algorithms for image segmentation.
title_full Harmony search-based fuzzy clustering algorithms for image segmentation.
title_fullStr Harmony search-based fuzzy clustering algorithms for image segmentation.
title_full_unstemmed Harmony search-based fuzzy clustering algorithms for image segmentation.
title_sort harmony search-based fuzzy clustering algorithms for image segmentation.
publishDate 2011
url http://eprints.usm.my/42978/1/Pages_from_HARMONY_SEARCH-BASED_FUZZY.pdf
http://eprints.usm.my/42978/
_version_ 1643710629280743424
score 13.18916

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