Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис:
http://hdl.handle.net/20.500.12188/23159
Наслов: | Hierarchical classification of diatom images using ensembles of predictive clustering trees | Authors: | Dimitrovski, Ivica Kocev, Dragi Loshkovska, Suzana Djeroski, Sasho |
Keywords: | Diatoms Automatic image annotation Hierarchical classification Predictive clustering trees Feature extraction from images | Issue Date: | 10-сеп-2011 | Publisher: | Elsevier | Journal: | Ecological Informatics | Abstract: | This paper presents a hierarchical multi-label classification (HMC) system for diatom image classification. HMC is a variant of classification where an instance may belong to multiple classes at the same time and these classes/labels are organized in a hierarchy. Our approach to HMC exploits the classification hierarchy by building a single predictive clustering tree (PCT) that can simultaneously predict all different levels in the hierarchy of taxonomic ranks: genus, species, variety, and form. Hence, PCTs are very efficient: a single classifier is valid for the hierarchical classification scheme as a whole. To improve the predictive performance of the PCTs, we construct ensembles of PCTs. We evaluate our system on the ADIAC database of diatom images. We apply several feature extraction techniques that can be used in the context of diatom images. Moreover, we investigate whether the combination of these techniques increases predictive performance. The results show that ensembles of PCTs have better predictive performance and are more efficient than SVMs. Furthermore, the proposed system outperforms the most widely used approaches for image annotation. Finally, we demonstrate how the system can be used by taxonomists to annotate new diatom images. | URI: | http://hdl.handle.net/20.500.12188/23159 |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
Files in This Item:
File | Опис | Size | Format | |
---|---|---|---|---|
10.1.1.723.3981.pdf | 1.03 MB | Adobe PDF | View/Open |
Записите во DSpace се заштитени со авторски права, со сите права задржани, освен ако не е поинаку наведено.