Zoltán Tóth

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We have developed a new stochastic image rendering method for the compression, description and segmentation of images. This paintbrush-like image transformation is based on a random searching to insert brush-strokes into a generated image at decreasing scale of brush-sizes, without predefined models or interaction. We introduced a sequential multiscale(More)
In this paper the GREDEA system is presented. The main idea behind it is that with the help of evolutionary algorithms a grammatical description of the blood circulation of the human retina can be inferred. The system uses parametric Lindenmayer systems as description language. It can be applied on patients with diabetes who need to be monitored over long(More)
Herein, we propose a new content based image retrieval method. The novelty of our approach lies in the applied image similarity measure : Unlike traditional features like color, texture or shape, our measure is based on a painted representation of the original image. We use paintbrush stroke parameters as features. These strokes are produced by a stochastic(More)
An automatic method is presented in order to detect lung nodules in PET-CT studies. Using the foreground and background mean ratio independently in every nodule, we can detect the region of the nodules properly. The size and intensity of the lesions do not affect the result of the algorithm, although size constraints are present in the final classification(More)
A paintbrush-like image transformation is proposed in this paper. It is based on a random searching to insert brush-strokes into a generated image at decreasing scale of brush-sizes, without predefined models or interaction. One of the goals of the method is to transform the image into a representation that is very similar to the human sensation of artistic(More)
In this paper the GREDEA system is presented. The main idea behind it is that with the help of evolutionary algorithms a grammatical description of the blood circulation of the human retina can be inferred. The system uses parametric Lindenmayer systems as description language. It can be applied on patients with diabetes who need to be monitored over long(More)
Describes a solution of the inverse problem for parametric Lindenmayer systems (L-systems) with genetic algorithms. The inverse problem studied is that of evolving Lindenmayer grammars to describe plants. A genetic algorithm is used to evolve the rewriting rules and the set of system parameters. In this paper, we present on extension of the solution of G.(More)
Version control systems store the whole history of the source code. Since the source code of a system is organized into files and folders, the history tells us the concerned files and their changed lines only but software engineers are also interested in which source code elements (e.g. classes or methods) are affected by a change. Unfortunately, in most(More)
In this paper the Generic Evolutionary Algorithms Programming Library (GEA) system is evaluated via a comparison with other genetic programming libraries based on test functions. The purpose of the GEA system is to provide researchers with an easy-to-use and extendable programming library which can solve optimization problems by means of evolutionary(More)