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...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | 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 |
| _version_ | 1848884088754143232 |
|---|---|
| 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 |
| building | USM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T19:01:09Z |
| format | Thesis |
| id | usm-59114 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:01:09Z |
| publishDate | 2022 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-591142023-08-14T03:01:35Z http://eprints.usm.my/59114/ Landmark Image Discovery Using Network Clustering" 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 NonPeerReviewed application/pdf en http://eprints.usm.my/59114/1/24%20Pages%20from%20ALA%E2%80%99A%20AHMED%20MOHAMMED%20AL-ZOU%E2%80%99BI%20-%20TESIS.pdf Mohammed Al-Zou’Bi, Ala’A Ahmed (2022) Landmark Image Discovery Using Network Clustering". PhD thesis, Perpustakaan Hamzah Sendut. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Mohammed Al-Zou’Bi, Ala’A Ahmed Landmark Image Discovery Using Network Clustering" |
| title | 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_short | Landmark Image Discovery Using Network Clustering" |
| title_sort | landmark image discovery using network clustering" |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | 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 |