Landmark Image Discovery Using Network Clustering"

Significant amounts of Internet photo collections are stored online and continue to grow rapidly. This wealth and availability of visual information enable the development of several computer vision applications. Therefore, there is a need for efficient techniques for structuring and organizing t...

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Main Author:	Mohammed Al-Zou’Bi, Ala’A Ahmed
Format:	Thesis
Language:	English
Published:	2022
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/59114/1/24%20Pages%20from%20ALA%E2%80%99A%20AHMED%20MOHAMMED%20AL-ZOU%E2%80%99BI%20-%20TESIS.pdf
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id	my-usm-ep.59114
record_format	uketd_dc
spelling	my-usm-ep.591142023-08-14T03:01:35Z Landmark Image Discovery Using Network Clustering" 2022-03 Mohammed Al-Zou’Bi, Ala’A Ahmed QA75.5-76.95 Electronic computers. Computer science Significant amounts of Internet photo collections are stored online and continue to grow rapidly. This wealth and availability of visual information enable the development of several computer vision applications. Therefore, there is a need for efficient techniques for structuring and organizing this large number of images. In particular, landmark images form a large portion of such collections. Mining of landmark images relies on clustering to group large-scale image collections by the object they depict. The grouping process is a very challenging task due to the variations in the object’s appearance, which can be caused by illumination conditions, differences in scale and imaging viewpoint. 2022-03 Thesis http://eprints.usm.my/59114/ http://eprints.usm.my/59114/1/24%20Pages%20from%20ALA%E2%80%99A%20AHMED%20MOHAMMED%20AL-ZOU%E2%80%99BI%20-%20TESIS.pdf application/pdf en public phd doctoral Perpustakaan Hamzah Sendut Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Mohammed Al-Zou’Bi, Ala’A Ahmed Landmark Image Discovery Using Network Clustering"
description	Significant amounts of Internet photo collections are stored online and continue to grow rapidly. This wealth and availability of visual information enable the development of several computer vision applications. Therefore, there is a need for efficient techniques for structuring and organizing this large number of images. In particular, landmark images form a large portion of such collections. Mining of landmark images relies on clustering to group large-scale image collections by the object they depict. The grouping process is a very challenging task due to the variations in the object’s appearance, which can be caused by illumination conditions, differences in scale and imaging viewpoint.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohammed Al-Zou’Bi, Ala’A Ahmed
author_facet	Mohammed Al-Zou’Bi, Ala’A Ahmed
author_sort	Mohammed Al-Zou’Bi, Ala’A Ahmed
title	Landmark Image Discovery Using Network Clustering"
title_short	Landmark Image Discovery Using Network Clustering"
title_full	Landmark Image Discovery Using Network Clustering"
title_fullStr	Landmark Image Discovery Using Network Clustering"
title_full_unstemmed	Landmark Image Discovery Using Network Clustering"
title_sort	landmark image discovery using network clustering"
granting_institution	Perpustakaan Hamzah Sendut
granting_department	Pusat Pengajian Sains Komputer
publishDate	2022
url	http://eprints.usm.my/59114/1/24%20Pages%20from%20ALA%E2%80%99A%20AHMED%20MOHAMMED%20AL-ZOU%E2%80%99BI%20-%20TESIS.pdf
_version_	1776101248895811584

Landmark Image Discovery Using Network Clustering"

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