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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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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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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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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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Identification of emotional state using speech signal analysis
Navrátil, Michal ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis deals with the analysis of human emotional states speaker by the help of analyse speech signals. The thesis has two parts. In the first part, the process of speech generating is described in addition to the description of the commonly used pre-processing methods such as denoising or preemphasis. The first part also deals with the major and minor prosody features, these features are: the fundamental frequency, energy, spectral features and time domain features such as the speech rate. The second part of this thesis deals with a task of emotion recognition from the speech signal. When we accumulate sufficient of the number of recordings emotive state will be able to rekognize emotive state with high probability. All project is prepared for use in real time. The last part of this thesis thesis contains description and results of the experiments made on a large number of speech records.
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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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Aplikace metod strojového učení na dolování znalosti z dat
Kraus, Jan
The diploma thesis deals with the area of data mining applied to large collections of textual data. Specifically the thesis is focused on sentiment analysis based on the user's subjective verbal assessment in natural language. The first part of the diploma thesis introduces the reader to basic terms of machine learning and data mining applied particularly to large textual data collections. Following is the description of textual data preprocessing methods and principles of machine learning algorithms. In the practical part of this thesis there are experiments designed and subsequently executed using the SPSS Modeler tool. The experimental part is focused especially on identification of significant attributes and recongnition of relationships between them. The emphasis is put especially on thorough interpretation of the results obtained.
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