|
|
Cluster analysis in the field of pathological speech signal processing
Čapek, Karel ; Mžourek, Zdeněk (referee) ; Galáž, Zoltán (advisor)
The bachelor thesis deals with the calculation of speech features that quantifies the degradation of speech production caused by the presence of certain speech pathology and the subsequent clasification of considered speech pathologies into several groups using the k-means algorithm. The purpose was to find the groups of pathologies that in spite of possible differences in the origin do affect phonation and articulation skills of the speakers and damage the quality of speech. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Furthermore, the preliminary analysis was applied to the featuresin order to select the features to best characterize the degradation of speech production. Finally, the selected features were used to find the resulting groups of pathologies using k-means algorithm.
|
|
|
Manifestation of physiological noise in fMRI data
Skoupý, Radim ; Mareček, Radek (referee) ; Lamoš, Martin (advisor)
In this bachelor thesis I deal with the manifestations of physiological noise in fMRI data. The work includes the basic theory of BOLD signal - his character, dealing with the processing of measured data, the possibilities of their treatment, filtration and formation of the resulting statistical parametric maps. The key part is studing possibilities of physiological noise filtering method Retroicor that models physiological noise based on sine and cosine basis functions.
|
|
|
Visualization of 3D data in biomedical applications
Karzel, Michal ; Harabiš, Vratislav (referee) ; Štohanzlová, Petra (advisor)
This thesis describes the basic principle of optical coherence tomography and prepro- cessing of the measured raw data. Preprocessing is focused mainly on noise filtration, removing artifacts, normalization, conversion and compression of raw data. In this way preprocessed data is saved in a *. PFRG file as ”preprocessed fringe data”. Those pre- processed data will be visualised by simply software, which support three methods of visualisation. Volume data represented by voxels. Reconstruction of volume by marching cube algorithm. Cuts through volume along X, Y and Z axis.
|
|
|
Biometric fingerprint liveness detection
Jurek, Jakub ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This project deals with general biometrics issues focusing on fingerprint biometrics, with description of dermal papillae and principles of fingerprint sensors. Next this work deals with fingerprint liveness detection issues, including description of methods of detection. Next this work describes chosen features for own detection, used database of fingerprints and own algorithm for image pre-processing. Furthermore neural network classifier for liveness detection with chosen features is decribed followed by statistic evaluation of the chosen features and detection results as well as description of the created graphical user interface.
|
|
|
Preprocessing and Transformation of Text Data Collections
Maruna, Viktor ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with the issue of text-mining, mostly focused on preprocessing and transformation. In theoretical part there are contained information about development and principles of text-mining processes, text data collections and use in practice. The next part of this thesis describes in detail single steps of preprocessing and transformation of text data collections. In the final parts there are reviews of application development, testing and personal view on this thesis.
|
|
| |
|
|
Textual Data Clustering Methods
Miloš, Roman ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
Clustering of text data is one of tasks of text mining. It divides documents into the different categories that are based on their similarities. These categories help to easily search in the documents. This thesis describes the current methods that are used for the text document clustering. From these methods we chose Simultaneous keyword identification and clustering of text documents (SKWIC). It should achieve better results than the standard clustering algorithms such as k-means. There is designed and implemented an application for this algorithm. In the end, we compare SKWIC with a k-means algorithm.
|
|
|
Scene Analysis Based on the 2D Images
Hejtmánek, Martin ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
This thesis deals with an object surface analysis in a simple scene represented by two-dimensional raster image. It summarizes the most common methods used within this branch of information technology and explains both their advantages and drawbacks. It introduces the design of an surface profile analysis algorithm based on the lighting analysis using knowledge and experiences from previous work. It contains a detailed description of the implemented algorithm and discusses the experimental results. It also brings up options for the possible enhancement of the projected algorithm.
|
|
|
Knowledge Discovery from Web Logs
Vlk, Vladimír ; Očenášek, Pavel (referee) ; Bartík, Vladimír (advisor)
This master's thesis deals with creating of an application, goal of which is to perform data preprocessing of web logs and finding association rules in them. The first part deals with the concept of Web mining. The second part is devoted to Web usage mining and notions related to it. The third part deals with design of the application. The forth section is devoted to describing the implementation of the application. The last section deals with experimentation with the application and results interpretation.
|
|
|
Web Mining - Clustering
Rychnovský, Martin ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This work presents the topic of data mining on the web. It is focused on clustering. The aim of this project was to study the field of clustering and to implement clustering through the k-means algorithm. Then, the algorithm was tested on a dataset of text documents and on data extracted from web. This clustering method was implemented by means of Java technologies.
|
guest ::
