Milena Petkovic

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Content-based video retrieval is emerging as an important part in the process of utilization of various multimedia documents. In this report we present a novel system for the automatic indexing and content-based retrieval of multimedia documents. We chose the domain of Formula 1 sport videos because the manual annotation of Formula 1 races is complicated(More)
In this paper, Support Vector Machines (SVMs) are applied in predicting electrical energy consumption in the atmospheric distillation of oil refining at a particular oil refinery. During cross-validation process of the SVM training Particle Swarm Optimization (PSO) algorithm was utilized in selection of free SVM kernel parameters. Incorporation of PSO into(More)
In this paper, Support Vector Machines (SVMs) are applied in predicting energy consumption in the first phase of oil refining at a particular oil refinery. During cross-validation process of the SVM training Particle Swarm Optimization (PSO) algorithm was utilized in selection of free SVM parameters, widths of radial basis functions to be exact.(More)
In recent years, research in video databases has increased greatly, but relatively little work has been done in the area of semantic content-based retrieval. In this paper, we present a framework for video modelling with emphasis on semantic content of video data. The video data model presented distinguishes four layers: the raw data layer, the feature(More)
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