Karla Brkic

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There are numerous classification methods developed in the field of machine learning. Some of these methods, such as artificial neural networks and support vector machines, are used extensively in biomedical time-series classification. Other methods have been used less often for no apparent reason. The aim of this work is to examine the applicability of(More)
We introduce a novel local spatio-temporal descriptor intended to model the spatio-temporal behavior of a tracked object of interest in a general manner. The basic idea of the descriptor is the accumulation of histograms of an image function value through time. The histograms are calculated over a regular grid of patches inside the bounding box of the(More)
This expert paper describes the characteristics of six most used free software tools for general data mining that are available today: RapidMiner, R, Weka, KNIME, Orange, and scikit-learn. The goal is to provide the interested researcher with all the important pros and cons regarding the use of a particular tool. A comparison of the implemented algorithms(More)
—This paper investigates classification of traffic scenes in a very low bandwidth scenario, where an image should be coded by a small number of features. We introduce a novel dataset, called the FM1 dataset, consisting of 5615 images of eight different traffic scenes: open highway, open road, settlement, tunnel, tunnel exit, toll booth, heavy traffic and(More)
We consider the task of automatic detection and recognition of traffic signs in video. We show that successful off-the-shelf detection (Viola-Jones) and classification (SVM) systems yield unsatisfactory results. Our main concern are high false positive detection rates which occur due to sparseness of the traffic signs in videos. We address the problem by(More)
—This paper proposes combining spatio-temporal appearance (STA) descriptors with optical flow for human action recognition. The STA descriptors are local histogram-based descriptors of space-time, suitable for building a partial representation of arbitrary spatio-temporal phenomena. Because of the possibility of iterative refinement, they are interesting in(More)
—Automated grading of multiple-choice exams is of great interest in university courses with a large number of students. We consider an existing system in which exams are automatically graded using simple answer sheets that are annotated by the student. A sheet consists of a series of circles representing possible answers. As annotation errors are possible,(More)