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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2022
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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 |