Suzana Loskovska

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In this paper, we describe an approach for the automatic medical annotation task of the 2008 CLEF cross-language image retrieval campaign (ImageCLEF). The data comprise 12076 fully annotated images according to the IRMA code. This work is focused on the process of feature extraction from images and hierarchical multi-label classification. To extract(More)
a r t i c l e i n f o 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(More)
In this paper, we present the approach that we applied to the medical modality classification tasks at the ImageCLEF evaluation forum. More specifically, we used the modality classification databases from the ImageCLEF competitions in 2011, 2012 and 2013, described by four visual and one textual types of features, and combinations thereof. We used local(More)
Predictive models make predictions about values of data using known results from different data, while frequent itemsets describe properties of a subset of the data and are descriptive in nature. In this paper we present a method of building predictive models by using frequency information from frequent itemsets. Modifications were done on three standard(More)
The research was undertaken having in consideration two hypothesis. The first hypothesis is that integration of virtual learning environment (VLE) and integrated developing environment (IDE) for programming in Java language will contribute in improving the efficiency and quality in learning because of the enhanced graphical user interface and the "hands on(More)
This article is concerned with the classes of the Constraint Solving Engine and a Constraint Programming Library for problems that can be defined as Constraint Satisfaction Problems. The theoretical and mathematical foundations of our ideas and the problem solving process are explained. Among the first problems that were solved was the Traveling Salesman(More)
In this paper we depict an implemented system for medical image retrieval. Our system performs retrieval based on both textual and visual content, separately and combined, using advanced encoding and quantization techniques. The text-based retrieval subsystem uses textual data acquired from an image’s corresponding article to generate a suitable(More)
This paper presents the details of the participation of FCSE (Faculty of Computer Science and Engineering) research team in ImageCLEF 2012 medical retrieval task. We investigated by evaluating different weighting models for text retrieval. In the case of the visual retrieval, we focused on extracting low-level features and examining their performance. For,(More)
In this paper we introduce an application layer for mobile devices that delivers knowledge sharing and remote collaboration to the end users. This layer is a part of a much wider knowledge sharing system called Internet Medical Consultant. Our main focus is on the user interface and data processing according to the mobility issues of the application. This(More)