Publication: Landmark Image Discovery Using Network Clustering
dc.contributor.author | Mohammed Al-Zou’Bi, Ala’A Ahmed | |
dc.date.accessioned | 2023-08-14T03:01:26Z | |
dc.date.available | 2023-08-14T03:01:26Z | |
dc.date.issued | 2022-03 | |
dc.description.abstract | 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. | |
dc.identifier.uri | https://erepo.usm.my/handle/123456789/17257 | |
dc.title | Landmark Image Discovery Using Network Clustering | |
dc.type | Resource Types::text::thesis::doctoral thesis | |
dspace.entity.type | Publication | |
oairecerif.author.affiliation | Universiti Sains Malaysia |
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