Academic
Publications
Hierarchical classification architectures applied to Magnetic Resonance Images

Hierarchical classification architectures applied to Magnetic Resonance Images,Katarina Trojacanec,Gjorgji Madjarov,Suzana Loskovska,Dejan Gjorgjevikj

Hierarchical classification architectures applied to Magnetic Resonance Images  
BibTex | RIS | RefWorks Download
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.
Published in 2011.
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.