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Feature extraction from image data
Uher, Václav ; Beneš, Radek (referee) ; Burget, Radim (advisor)
Image processing is one area of signal analysis. This thesis is involved in feature extraction from image data and its implementation using Java programming language. The main contribution of this thesis lies in develop features extractors and their implementation in the program RapidMiner. The result is a robust tool for image analysis. The functionality of each operator is tested on mammogram images. A function model was developed for the removal of artifacts from the mammography images. The success rate of removal is comparable with other similar works. Furthermore, learning algorithms were compared on example detection of ventricle in ultrasound image.
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Decision trees
Patera, Jan ; Sáblík, Václav (referee) ; Honzík, Petr (advisor)
This diploma thesis presents description on several algorithms for decision trees induction and software RapidMiner. The first part of the thesis deals with partition and terminology of decision trees. There’re described all algorithms for decision tree construction in RapidMiner. The second part deals with implementation and comparison of chosen algorithms. The application was developed in C++. Based on the real datesets the comparisson of different algorithms was realized using Rapid Miner 4.0.
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Using of Data Mining Method for Analysis of Social Networks
Novosad, Andrej ; Očenášek, Pavel (referee) ; Bartík, Vladimír (advisor)
Thesis discusses data mining the social media. It gives an introduction about the topic of data mining and possible mining methods. Thesis also explores social media and social networks, what are they able to offer and what problems do they bring. Three different APIs of three social networking sites are examined with their opportunities they provide for data mining. Techniques of text mining and document classification are explored. An implementation of a web application that mines data from social site Twitter using the algorithm SVM is being described. Implemented application is classifying tweets based on their text where classes represent tweets' continents of origin. Several experiments executed both in RapidMiner software and in implemented web application are then proposed and their results examined.
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Knowledge Discovery in Multimedia Databases
Málik, Peter ; Bartík, Vladimír (referee) ; Chmelař, Petr (advisor)
This master"s thesis deals with the knowledge discovery in multimedia databases. It contains general principles of knowledge discovery in databases, especially methods of cluster analysis used for data mining in large and multidimensional databases are described here. The next chapter contains introduction to multimedia databases, focusing on the extraction of low level features from images and video data. The practical part is then an implementation of the methods BIRCH, DBSCAN and k-means for cluster analysis. Final part is dedicated to experiments above TRECVid 2008 dataset and description of achievements.
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Semantic Recognition of Comments on the Web
Stříteský, Radek ; Harár, Pavol (referee) ; Povoda, Lukáš (advisor)
The main goal of this paper is the identification of comments on internet websites. The theoretical part is focused on artificial intelligence, mainly classifiers are described there. The practical part deals with creation of training database, which is formed by using generators of features. A generated feature might be for example a title of the HTML element where the comment is. The training database is created by input of classifiers. The result of this paper is testing classifiers in the RapidMiner program.
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Computer analysis of medical image data
Krajčír, Róbert ; Šmirg, Ondřej (referee) ; Uher, Václav (advisor)
This work deals with medical image analysis, using variety of statisic and numeric methods implemented in Eclipse and Rapidminer environments in Java programming language. Sets of images (slices), which are used here, are the results of magnetic resonance brain examination of several subejcts. Segments in this 3D image are analyzed and some local features are computed, based on which data sets for use in training algorythms are generated. The ability of successful identification of healthy or unhealthy tissues is then practically tested using available data.
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Stemming Methods Used in Text Mining
Adámek, Tomáš ; Chmelař, Petr (referee) ; Bartík, Vladimír (advisor)
The main theme of this master's thesis is a description of text mining. This document is specialized to English texts and their automatic data preprocessing. The main part of this thesis analyses various stemming algorithms (Lovins, Porter and Paice/Husk). Stemming is a procedure for automatic conflating semantically related terms together via the use of rule sets. Next part of this thesis describes design of an application for various types of stemming algorithms. Application is based on the Java platform with using of graphic library Swing and MVC architecture. Next chapter contains description of implementation of the application and stemming algorithms. In the last part of this master's thesis experiments with stemming algorithms and comparing the algorithm from viewpoint to the results of classification the text are described.
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Methods for Segmented Image Processing
Štěrba, Radek ; Číka, Petr (referee) ; Zukal, Martin (advisor)
This work deals with the representation of segmented images using graphs. Different segmentation methods used in processing visual information are described here. Today is mathematics increasingly needed. This fact is not omitted, basic information of graph theory are described in this paper. The second part of this work is practical. It contains a survey of libraries processing graphs. Further the data structures for describing the segmented image are described. Last but not least, there is also described the formation and properties of the operators designed for environment RapidMiner that fill these structures.
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Open-source systems for image processing
Slinták, Vlastimil ; Zukal, Martin (referee) ; Mikulka, Jan (advisor)
The aim of this document is to describe open-source libraries for image processing — ITK, VTK and OpenCV. Their architectures are described and it is shown how to compile and use them in real applications. It also provides basic description of algorithms for image processing. In the second part of this document, we try to use ITK library with data-mining environment RapidMiner.
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Segmentation of microscopic brain structures
Láska, Samuel ; Uher, Václav (referee) ; Burget, Radim (advisor)
This thesis is involved in image processing of medical data and its implementation using Java programming language. The main contribution of this thesis is creation of algorithms for feature extraction from 3D data and subsequent verification of the results for the issue of imagining 3D brain data, and creation of image filters and their implementation in the program RapidMiner. Consequently, the segmentation process is created at the 2D and 3D level, and output of 3D level segmentation are segmented brain structures. Furthermore, segmentation algorithms were compared on the basis of the final form of segmented structures and this approach was compared with other works.
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