Dmytro Peleshko

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The new learning-based image super-resolution method is described in this article. The process of increasing the resolution of video frames or images from a set according to the method is based on the weight coefficients of synaptic connections. These coefficients are obtained by the learning neural-like structure on a pair of images of low and high(More)
In this paper we propose architecture of hybrid generalized additive neuro-fuzzy system. Such system is hybrid of the neuro-fuzzy system of Wang-Mendel and the generalized additive models of Hastie-Tibshirani. Proposed hybrid generalized additive neuro-fuzzy system can be used for solving different tasks of computational intelligence and data stream mining.(More)
One of the primary tasks of videoframes processing of digital videostreams is to quantify the geometric structure of moving objects, in order to extract information from videostreams frames. In this paper we purpose a recursive algorithms that are based on morphological conditional dilation and conditional erosion operations. Practical implementation of(More)
In the paper the problem of on-line diagnostics and properties change detection of systems whose output signal is multidimensional non-stationary stochastic sequence is considered. The six-layer diagnostic neuro-fuzzy system is proposed. The first layer of this system consists of membership functions blocks, the second layer provides aggregation of(More)
The paper describes the method image superresolution from two frames on the basis of aggregate divergence matrix elements of the theory and genetic algorithms. Shows different ways for building oversampling images algorithms based on the proposed method. Experimentally established the effectiveness of the procedures oversampling images at high zoom(More)
A method of tracking objects in multi CCTV, based on the use of the characteristic features of color, proximity and path is studied. The method's essence lies in resolving of the extreme problem concerning the generalized criteria, built on metrics in the field of each feature. The crucial advantage of the proposed method is ensuring of a sufficient level(More)
This thesis is devoted to development of visitor's queue density analysis and registration method for a retail videosurveillance systems. Developed method of foreground segmentation is based on initial background modeling, selective temporal median filter and local binary patterns. Based on the literature review, a problem statement has been examined and(More)