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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.
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Preprocessing of ophthalmology images for image registration
Orešanská, Hana ; Sekora, Jiří (referee) ; Harabiš, Vratislav (advisor)
The aim of my thesis was research of the ophthalmology images processing. These methods contains image filtration, detection of important points in the image and registration. Image adjustment and the follow up registration is very important to find some deseases (e.g. glaucoma, where is a change of nervous threads going from retina ). For the image changes and registrations was made computer programme (Matlab, Graphical User Interface), where the user can try the different methods decribed in teoretical part of thesis.
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Software for visualization and processing of volumetric data
Viktorínová, Michaela ; Jakubíček, Roman (referee) ; Harabiš, Vratislav (advisor)
The work summarizes the possibilities of volume data displaying. It deals with the scalar type of volume algorithms, which are then divided into techniques of indirect and direct rendering of volume data. From indirect techniques the Marching Cubes method is mentioned. Direct techniques are further divided into trivial and advanced algorithms. The practical part describes the design, implementation and evaluation of the functionality of implemented program that uses trivial methods. The overall evaluation consists of partial evaluations of the computational complexity, the memory load and the quality of final rendering while using different methods and types of input volume data.
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Basic fingerprint liveness detection
Horák, Tomáš ; Smital, Lukáš (referee) ; Kašpar, Jakub (advisor)
This work focuses on recognizing fingerprints liveness based purely on software-methods evaluating symptoms from just one fingerprint image. At first in this work was described the issue of biometry as such, comparing the advantages and disadvantages of such systems. Next part deal with more detailed process of fingerprint biometry including papillary lines and overall fingerprints as such. In the next phase, the problems and utilization of both software and hardware methods are discussed, including principles of individual approaches. This part is followed by a selection of used fingertip symptoms. This is followed by the practical part and the LivDet 2011 database, which was used for finger recognition. In the practical part is also described the used neural network capturing minor differences in fingerprints according to 13 symptoms.
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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.
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Segmentation in microscopic images
Vlk, Jaroslav ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Work studying the properties of microscopic images and then the following applies in the segmentation of the image. Work is trying to use a simpler methods image processing mainly. At the same time, deals with methods for preprocessing image. In the choice of methods and the use of emphasis on speed and simplicity of calculation.
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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.
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Automatic / Automated recogniton of emotional states based on utterance analysis
Pfeifer, Leon ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis deals with the analysis of human emotional states. The thesis consists of three parts. The first part is charcterize, the process of speech generating, from phonetic and psychological poin of view. In the second part there are proccesed metods and contextual things.(preprocessing of signal, voice activity detector). For calculation fundamental Frequency it was used metod of central clipping, another used metod is formant frequency analyse and the last is metod of determinatin of nuber of thorns and planes. In the thirt part there are proccesesed results of measurements performed by particural metods. It was scorred five different emotional states: neutral, anger, happiness, sadness and surprise. At the end of this part there are discussed results for each metod.
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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.
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