Numerical optimization of multimodal or otherwise nontrivial functions has stayed around the peak of the interest of many researchers for a long time. One of the promising methods that appeared is the hybrid approach of the Learnable Evolution Model that combines the well-established ways of artificial intelligence and machine learning with recently popular and efective methods of evolutionary programming. In this work, the method itself was reviewed with respect to what has been already implemented and tested and several possible new implementations of the method were proposed and some of them consequently implemented. The resulting program was then tested against a set of chosen nontrivial real-valued functions and its results were compared to those achieved with EDA algorithms.

Ultrasound imaging is widely used in medical examination. However, the interpretation of images is not trivial and requires much experience. In this thesis, various techniques for enhancement of visual quality of ultrasound images are presented. Several basic and advanced methods that may simplify the visual diagnosis are described. Finally, an interactive application is designed and implemented for simple usage of presented methods.

This work focuses on classification and recognition of traffic signs in image. It describes briefly some used methods a deeply describes chosen system including extensions and method for creating models needed for classification. There's described implementation of library and demonstration program including important pieces of knowledge discovered during development. There're also results of some experiments and possible enhancements in conclusion.

This thesis deals with the extension of the bachelor's thesis Movie Database. I focus on the practical application of data mining as well as the personalization of this information system. In data mining, I will use the data accrued during the operation site. The introduction summarizes the concepts of data mining. In the second section  outlines new developments in web applications followed by an overview and description of the new site's features.  The last chapters are devoted to  the description of the design and the implementation of data mining techniques. The conclusion gives the achieved results.

This diploma thesis deals with acceleration of advanced genetic algorithm. For implementation, discrete and continuos versions of UMDA genetic algorithm were chosen. The main part of the acceleration is the utilization of SSE instruction set. Using this set, the functions for calculating fitness and new population sampling were accelerated in particular. Then the pseudorandom number generator that also uses SSE instruction set was implemented.  The discrete algorithm reached the speed of up to 4,6 after this implementation. Finally, the algorithms were modified so that the system  OpenMP could be used, which enables the running of blocks of code in more threads. The continuous version of algorithm is not convenient for parallelization, because computational complexity of that algorithm is low. In comparison, the discrete versions of algorithm are really appropriate for parallelization. Both the implemented versions reached the total acceleration of up to 4,9 and 7,2.

This paper deals about AdaBoost algorithm, which is used to create a strong classification function using a number of weak classifiers. We familiarize ourselves with modifications of AdaBoost, namely Real AdaBoost, WaldBoost, FloatBoost and TCAcu. These modifications improve some of the properties of algorithm AdaBoost. We discuss some properties of feature and weak classifiers. We show a class of tasks for which AdaBoost algorithm is applicable. We indicate implementation of the library containing that method and we present some tests performed on the implemented library.

In my diploma thesis, which is called "University Qualification Thesis: MASTER'S DEGREE DIPLOMA THESIS - STUDIO PART (D), I try to fulfill the protocol, which is specified in the following points: - Get grade "D" from my diploma thesis - studio part, - If I don't get grade "D" from my diploma thesis - studio part, I did not fulfill the assignment and the goal. Therefore, the project should not be considered as successful and should be graded "F". The thesis doesn't have a visual form. The project itself is just the "concept" described in the two points mentioned above in the text including all the consequences and its progression. My creative contribution is only to induce the situation. This text is just a text part of the documentation used for easier understanding and for contextualizing. Thus, this text is a lexical (and graphical in case of the diagram shown in the full text) comment on the project and it should not be subject to evaluation. Additional form of documentation of the project will be an audio recording of defense of this project taken by a record company. My speech during the defense is also not meant to be a performace as an art discipline and therefore should not be assessed.

The aim of this thesis is to propose methods for obtaining the additional vehicle parameters from the real-world traffic situations images and including existing information of the license plate and localization of the vehicle in the scene. The task is to use an existing installation of the camera systems based on data obtained from these devices to propose a new method of extraction of other vehicle's parameters. Solutions can be divided into two groups: 1. Methods for obtaining the features and methods of data evaluation which will lead to a vehicle's type identification based on a single image of the vehicle. 2. Methods for obtaining data of the vehicle's shape based on image sequence of passing vehicle.

This thesis deals with use of regression or classification based on support vector machines from machine learning field. SVMs predict values that are used for decisions of automatic trading system. Regression and classification are evaluated for their usability for decision making. Strategy is being then optimized, tested and evaluated on foreign exchange market Forex historic data set. Results are promising. Strategy could be used in combination with other strategy that would confirm decisions for entering and exiting trades.

The aim of this thesis is to create a cloud application for traffic analysis without knowing anything about the system. The only input is address of the web camera pointing at traffic. This application is build on existing solution which is further enhanced. New modules for removing obstacles (such as lamppost covering part of the road) and splitting overlapping cars were added. The whole cloud solution consists of multiple components which communicates by HTTP messages and are controlled by web interface.