Mariofanna G. Milanova

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In this paper, the application of CNN associative memories for 3D object recognition is presented. The main idea is to analyse the optical flow in an image sequence of an object. Several features of the optical flow between two succeeding images are calculated and merged to a time series of features for the whole image sequence. These features show several(More)
In many medical image segmentation applications identifying and extracting the region of interest (ROI) accurately is an important step. The usual approach to extract ROI is to apply image segmentation methods. In this paper, we focus on extracting ROI by segmentation based on visual attended locations. Chan-Vese active contour model is used for image(More)
We review a number of applications of computational intelligence to problems in bioinformatics and computational biology, including gene expression, gene selection, cancer classification, protein function prediction, multiple sequence alignment, and DNA fragment assembly. We discuss some representative methods to provide inspiring examples to illustrate how(More)
The paper presents a new method for extracting and positioning contours of moving objects. The method is applicable in the surveillance of elderly individuals and facilitates the detection of critical situations when the elderly individuals find themselves in need of immediate help. For this, single frames from the video sequence are extracted in regular(More)
This paper presents a new paradigm for signal decomposition and reconstruction that is based on the selection of a sparse set of basis functions. Based on recently reported results, we note that this framework is equivalent to approximating the signal using Support Vector Machines. Two different algorithms of modeling sensory activity within the barrel(More)