Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/19020
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Trojachanec, Katarina | en_US |
dc.contributor.author | Loshkovska, Suzana | en_US |
dc.contributor.author | Madjarov, Gjorgji | en_US |
dc.contributor.author | Gjorgjevikj, Dejan | en_US |
dc.date.accessioned | 2022-06-17T13:08:15Z | - |
dc.date.available | 2022-06-17T13:08:15Z | - |
dc.date.issued | 2011-06-27 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/19020 | - |
dc.description.abstract | The main goal of the paper is to explore hierarchical classification. The investigation is performed on the dataset of Magnetic Resonance Images (MRI) which is hierarchically organized. Generalized top-down hierarchical classification architecture is proposed in the paper. Additionally, two specific cases of the generalized architecture are explored: three-stage hierarchical architecture based on SVM and three-stage hierarchical architecture based on ANN. From the performed experiments, it is concluded that the SVM based scheme outperforms the ANN based scheme. Moreover, the gain of the investigation conducted in this paper becomes bigger with the possibilities given by the proposed generalized architecture for further investigations. | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Image classification, Hierarchical classification, Flat classification, MRI | en_US |
dc.title | Hierarchical classification architectures applied to Magnetic Resonance Images | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | Proceedings of the ITI 2011, 33rd International Conference on Information Technology Interfaces | en_US |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
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 |
Files in This Item:
File | Description | Size | Format | |
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ITI2011-10-08-315-with-cover-page-v2.pdf | 335.03 kB | Adobe PDF | View/Open |
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