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Utilization of artificial intelligence in vibrodiagnostics
Dočekalová, Petra ; Huzlík, Rostislav (referee) ; Zuth, Daniel (advisor)
The diploma thesis deals with machine learning, expert systems, fuzzy logic, genetic algorithms, neural networks and chaos theory, which fall into the category of artificial intelligence. The aim of this work is to describe and implement three different classification methods, according to which the data set will be processed. The GNU Octave software environment was chosen for the data application for licensing reasons. Further evaluate the success of data classification, including visualization. Three different classification methods are used for comparison, so that we can compare the processed data with each other.
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The Use of SVM in Environment of Financial Markets
Štechr, Vladislav ; Prochocká, Kristína (referee) ; Budík, Jan (advisor)
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.
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Image Texture Representation and Detection
Zachar, Tomáš ; Ševcovic, Jiří (referee) ; Španěl, Michal (advisor)
This bachelor's thesis presents methods used for texture classification and implements programme which is able to realize simple classification and which is capable of generating dynamic bank of filters according to actual texture library. For feature extraction is used combination of Gabor filters with Hu-moments. As classifier there is used algorithm SVM.
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Content Based Photo Search
Valenta, Martin ; Mlích, Jozef (referee) ; Španěl, Michal (advisor)
This work deals with methods appropriate to content based photo search, design and implementation of subsequent applications for searching buildings. Purpose of the application is to create an interactive guide to the city using a combination of Web and client technologies (mobile, desktop). There are subscribed in detail the steps of recognition. A key points of the image are extracted by SURF. A visual dictionary is calculated with k-means algorithm. The dictionary is weighted by TF- IDF. To describe the image data is used a Bag of Words method. The text also mentions the new trends in this area and summarizes the application design and implementation results achieved.
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Height Measurement in Digital Image
Olejár, Adam ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
The aim of this paper is a summary of the theory necessary for a modification, detection of person and the height calculation of the detected person in the image. These information were then used for implementation of the algoritm. The first half reveals teoretical problems and solutions. Shows the basic methods of image preprocessing and discusses the basic concepts of plane and projective geometry and transformations. Then describes the distortion, that brings into the picture imperfections of optical systems of cameras and the possibilities of removing them. Explains HOG algorithm and the actual method of calculating height of person detected in the image. The second half describes algoritm structure and statistical evaluation.
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The use of EEG in assessing the emotional state of a person
Strakoš, Libor ; Mézl, Martin (referee) ; Potočňák, Tomáš (advisor)
This thesis is focused on EEG processing and emotion classification within two-dimensional emotion space. First part consists of theoretical research about emotional responses of human subjects on sound, image and video stimuli. Emotions are examined from aspect of physiology and psychology. Furthermore technical overview of measurement, analysis and emotion classification within two-dimensional emotional space is discussed. Based on gathered knowledge measurement setup with audiovisual stimuli was designed and measured with two independent instruments – EGI GES400MR in laboratory conditions and Emotiv EPOC device in non-laboratory conditions. Signals were processed and emotions were classified based on chosen features. Performance of classifiers in multiple feature selection setups was evaluated.
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Comparison of Classification Methods
Dočekal, Martin ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
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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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Creation of New Prediction Units in Data Mining System on NetBeans Platform
Havlíček, David ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
The issue of this master's thesis is a creation of new prediction unit for existing system of knowledge discovery in database. The first part of project deal with general problems of knowledge discovery in database and predictive analysis. The second part of the project deal with system developed on FIT, for which is module implemented, used technologies, concept and implementation of mining module for this system. The solution is implemented in Java language and is a built on the NetBeans platform.
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Speech-signal-based recognition of type of transmission channel
Kopřiva, Tomáš ; Burget, Radim (referee) ; Atassi, Hicham (advisor)
This work deals with the classification of five different transmission channels by speech signal processing. The channels considered are: GSM, two PSTN channels and two VoIP channels. For the training and testing purposes, a speech database for the transmission channels called SPLAB_TranCh was constructed. The speech signals of this corpus originally come from well-known TIMIT database, where each utterance passed through each mentioned transmission channel. The main objective of this work is to find optimal features and classification accuracy that yield best classification accuracy. Several types of features, including MFCC, LPCC and spectral characteristics were put under examination. The best suprasegmental features were identified by using mRMR algorithm. Several classifiers were tested as well. The results suggested that the classification of transmission channel can be performed with high accuracy (around 90 %). Influence of adverse effects, which can occur during transmission, is also examined. Considered types of distortions are: saturation, thresholding, echo, crackling noises and different colors of noises and filters.
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