Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/19021
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Trojachanec, Katarina | en_US |
dc.contributor.author | Stojanova, Elena | en_US |
dc.contributor.author | Loshkovska, Suzana | en_US |
dc.contributor.author | Dimitrovski, Ivica | en_US |
dc.date.accessioned | 2022-06-17T13:11:28Z | - |
dc.date.available | 2022-06-17T13:11:28Z | - |
dc.date.issued | 2013 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/19021 | - |
dc.description.abstract | This paper focuses on applying multi-query single-group methods to improve the content based image retrieval performance. The Multi-query-Max and Multi-query-Avg methods were applied using different numbers of query examples, namely three, five, and ten. The dataset contained medical images. The results obtained from the multi-query methods are compared to the single-query approach. The multi-query outperformed the single-query approach in all cases, meaning three, five, and ten queries based retrieval. Additionally, the Multi-query-Max method gives the best results on the bases of MAP (Mean Average Precision) value, when for the feature extraction purposes the Edge Histogram Descriptor (EHD) is used. | en_US |
dc.publisher | Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia | en_US |
dc.title | Multi-query Content Based Medical Image Retrieval | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | CIIT 2013 | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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10CiiT-19.pdf | 306.53 kB | Adobe PDF | View/Open |
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