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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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Image-Based Licence Plate Recognition
Vacek, Michal ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
In first part thesis contains known methods of license plate detection. Preprocessing-based methods, AdaBoost-based methods and extremal region detection methods are described.Finally, there is a described and implemented own access using local detectors to creating visual vocabulary, which is used to plate recognition. All measurements are summarized on the end.
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Processing and Visualization of Mass Spectrums
Beneš, Ondřej ; Bendl, Jaroslav (referee) ; Martínek, Tomáš (advisor)
One of new techniques in the field of analytical chemistry, which has more and more practical use, is mass spectrometry imaging. With its ability to record representation of substances in samples during the tissue analyze arise problem with a lot of output data which needs to be handled programmatically. The goal of this work is to create an software for processing and visualization data of new standard imzML. As a part of the work, the field of mass spectrometry, primarily MALDI TOF mass spectrometry, is briefly introduced. There are also introduced some methods for mass spectrometry data preprocessing. The work also contains a summary of current state of available software for processing and visualization of mass spectrometry data. With requests from cooperating laboratory a novel software is designed and implemented, which besides the visualization itself, can preprocess the data for example data smoothing with Savitzky-Golay method, internal calibration or peak detection with continuous wavelet transformation. The software was successfully tested on real data sets.
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Preprocessing of ECG signals for detection of significant points
Kuběna, Zdeněk ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
Bachelor thesis Preprocessing of ECG signal for the detection of significant points is about the primary preprocessing of ECG signal, to allow the subsequent signal diagnostic. The main task of preprocessing is to suppress the artifacts of the ECG signal, that makes the further interpretation impossible. Because there is typically an additive mixture of useful signal and noise, the simplest preprocessing way is linear filtering using digital filters. This work describes the most common types of interference, which occurs during the ECG signal measuring. Then there is the issue of repression dismantled, and design of filters with their bank.
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Image processing with neural networks
Gróf, Zoltán ; Pohl, Jan (referee) ; Jirsík, Václav (advisor)
This bachelor’s thesis centralizes on the possible uses of neural networks in the field of computer vision. This work contains basic theoretic knowledge of the field of neural networks and image processing. It discusses how successfully can neural networks be applied through the separate steps of image processing, what kind of neural networks are suitable for these steps, and what are the problems that might appear with their use. The work discusses the fields of classification and image understanding in a more detailed level. It’s shown how the use of neural networks can be appropriate in these applications. An own program was created as part of this work to demonstrate the classification capabilities of neural networks. It’s shown a neural network is created and trained for the recognition of handwritten numbers. The trained neural network was subject to different tests, through which the conclusion was reached, that it works with a high success rate, but is sensitive to changes in the input objects: change of size and location. A number of possible solutions were designed for this problem.
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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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Realization of fingerprint scanner
Kovář, Martin ; Sekora, Jiří (referee) ; Mézl, Martin (advisor)
This master’s thesis deals with the issue of scanning human fingerprints, which is currently very topical and represents the most widespread biometric technology. The theoretical part of the work acquaints the reader with basics of dactyloscopy and biometrics and concerns technologies used for fingerprinting, image preprocessing methods and commercially available contactless optical scanners. The practical part is a realisation of a contactless optical scanner based on a Raspberry Pi minicomputer, implementation of preprocessing algorithms in Python and testing of the device from the perspective of image quality.
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Paralinguistic signals recognition in spoken dialogs
Mašek, Jan ; Míča, Ivan (referee) ; Atassi, Hicham (advisor)
This document describes the three methods for the detection and classification of paralinguistic expressions such as laughing and crying from usual speech by analysis of the audio signal. The database of records was originally designed for this purpose. When analyzing everyday dialogs, music might be included, so the database was extended by four new classes as speech, music, singing with music and usual speech with background music. Feature extraction, feature reduction and classification are common steps in recognizing for all three methods. Difference of the methods is given by classification process in detail. One classification of all six classes at once is proposed in the first method called straight approach. In the second method called decision tree oriented approach we are using five intuitive sub classifiers in the tree structure and the final method uses for classification emotion coupling approach. The best features were reduced by feature evaluation using F-ratio and GMM classifiers were used for the each classification part.
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Automatic recognition of the electrometer status from picture
HANZLÍK, Ondřej
This thesis deals with problems of recognition of an electrometer´s state from sensing image. It is tangibly about electrometer´s scanning by a mobile phone´s camera. There is a surface with an electrometer´s dial which is detected and on this surface the particular numbers are detected consequently. The numbers are recognized via neural network. For more information from this image there are used some techniques of image segmentation to check the status. For the classification of the segmentation´s outputs are used classification tools, especially a support vector machine (SVM) and neural networks. Problems of image segmentations are solved by using OpenCV library. OpenCV is used for the implementation of the vector machine either. Application is on Android platform. Part of the thesis is concerned in a creation of a desktop application which is instrumental towards testing of neural network. The thesis also describes how to save the necessary data gathering in the course of the recognition which are used for working with neural network. The part of the thesis also deals with running web which will be evolved for the opportunity to participate in the further development of the system. There is available a public repository with source codes created during implementation.
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