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Solving Optimization Tasks by PSO Algorithms
González, Marek ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
In this document we describe the Particle Swarm Optimization (PSO) and discuss its performance in solving optimization tasks. PSO is stochastic population-based computational method mainly focused on continuous optimization. We give an introduction to the field of optimization and provide a theoretical description of the PSO method. We have implemented the method in C/C++ and investigated the best working parameter set. The implementation is evaluated on clustering, travelling salesman problem, and function minimization case studies.
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Automatic Photography Categorization
Veľas, Martin ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with explicit data embeding is used for its efficiency. Finally, results of experiments with above mentioned techniques of the image categorization are discussed.
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System For Analysis of Biathlon Statistics
Zeman, Ondřej ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
The goal of this bachelor's thesis is to create a web application that downloads biathlon data and statistics and use the technique to get knowledge from data to get interesting and unusual information. In this work are solving descriptive and predictive mining tasks. Clustering algorithms have been used for descriptive mining tasks and for search patterns in course and shooting statistics. Prediction of race results is solved by using multiple linear regression. The application is implemented in Python. Web application is available at https://analysisofbiathlonstatistics.herokuapp.com.
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Author Disambiguation in the Domain of Scholarly Literature
Krygielová, Magdaléna ; Kolář, Dušan (referee) ; Burget, Radek (advisor)
Tato práce se zabývá desambiguací autorů v databázích odborné literatury. Z důvodu nejednoznačnosti jmen autorů se v těchto databázích vyskytují problémy s přisuzováním autorství publikací a tím spojenou analýzou citací, vlivu autorů apod. Tato práce se zabývá otázkou odhadu správného počtu autorů a zkoumá možnosti použití již existujících služeb. Součástí této práce je návrh metody pro desambiguaci autorů. Tato metoda byla implementována a evaluována v rámci systému CORE.
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Optical Character Recognition in Images
Kadlic, Pavel ; Mlích, Jozef (referee) ; Chmelař, Petr (advisor)
The bachelor's thesis focuses on detection, localization, tracking and extraction of text from images and videos. There are described algorithms achieving optical chacarcter recognition. The thesis deals with implementation of algorithms, selecting a suitable sample of test data and its evaluation.
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Integration, Visualization, and Mining from Data of World Countries
Dušek, Vladimír ; Rychlý, Marek (referee) ; Bartík, Vladimír (advisor)
This thesis explores the utilization of open data about countries around the world, particularly data in the areas of progress and quality of life. The goal was to design and implement a web application to present this data and further use the data for data mining. The integration and processing of data from open data sources were accomplished using the Apache Airflow platform. The Python framework FastAPI was used to create the API and the JavaScript library ReactJS was used to implement the web application. In the application, the indicators are categorized. Each of them can be displayed for different groups of countries, for different time periods, and in several visualizations. From the domain of data mining, clustering of countries based on a group of indicators and prediction of future development of selected indicators using regression analysis was performed. The final application is available at jakjsmenatom.cz.
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Software demo of unsupervised learning
Slezák, Milan ; Sáblík, Václav (referee) ; Honzík, Petr (advisor)
The bachelor's thesis introduces the use of unsupervised learning and presents possibilities of cluster analysis. Software demo of unsupervised learning is a part of this thesis. This program was made as a teaching aid. It consists several input databases with different data distributions on the basis of which it is possible to explain very easily elementary principles of cluster analysis and differences between hierarchical clustering and partitional clustering.
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Cluster analysis in mathematical software
Starý, Josef ; Karpíšek, Zdeněk (referee) ; Žák, Libor (advisor)
This bachelor thesis is focused on methods of cluster analysis in mathematical software. The goal is to describe basic methods of cluster analysis, to describe their implementation in mathematical software, to use the methods for clustering of prepared data and to compare the functionality of chosen software.
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Cluster Analysis Module of a Data Mining System
Hlosta, Martin ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with the design and implementation of a cluster analysis module for currently developing datamining system DataMiner on FIT BUT. So far, the system lacked cluster analysis module. The main objective of the thesis was therefore to extend the system of such a module. Together with me, Pavel Riedl worked on the module. We have created a common part for all the algorithms so that the system can be easily extended to other clustering algorithms. In the second part, I extended the clustering module by adding three density based clustering aglorithms - DBSCAN, OPTICS and DENCLUE. Algorithms have been implemented and appropriate sample data was chosen to verify theirs functionality.
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