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Interpreting the learning process of an atrial fibrillation classifier
Lichtblauová, Anna ; Ředina, Richard (referee) ; Novotná, Petra (advisor)
In the theoretical part of the bachelor thesis the problems of atrial fibrillation (AF) detection and principles of convolutional neural networks (CNN) are discussed. Next, two classifiers were created in the practical part. The first was designed to classify sinus rhythm, atrial fibrillation and other pathologies, while the second further distinguished the category "atrial fibrillation" according to whether it was present in the whole recording or only in a part of it. The resulting accuracies are 82.12 \% and 85.14 \% for the first and second classifiers, respectively.
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Automatic improvements of images from 1D gel electrophoresis
Kovář, Martin ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
In this bachelor’s thesis are explained the basic principles of electrophoresis and its modalities with focusing on 1D gel electrophoresis. It describes analysis of an electrophoreogram and causes of its possible distortion, and states specifications of applications of the method in microbiology, genomics and proteomics. The practical part presents development, optimization and outputs of a programme for automatic electrophoreogram analysis, which was created in Matlab environment. The analysis contains lane and band detection and computation of samples’ molecular weight. The ending of the thesis is constituted by evaluating efficiency of detection and accuracy of weight computation.
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New Models for Automatic Detection of Performance Degradation
Stupinský, Šimon ; Češka, Milan (referee) ; Rogalewicz, Adam (advisor)
Performance testing is a critical factor in the optimisation of programs during its development, but it is still not so well developed in comparison to functional testing. A framework Perun provides full automation of performance management, thereby contributing to the development of this area. We have introduced three non-parametric approaches to performance data modelling: regressogram, moving average and kernel regression, which were integrated within this framework. We try to achieve appropriate approximations of performance data using these techniques, without the assumption of dependence between two variables, which represents the main advantage in comparison to parametric techniques. Further, we have proposed and implemented two methods for automatic detection of performance changes, which works with all kinds of models within Perun . We have demonstrated our solutions on the real project ( Vim ), and on the set of the experimental cases, in which we compared proposed solutions with existing. We have achieved decreased time processing about two-thirds and an almost triple improvement in the fitness of data modelling with new modelling approaches. The proposed detection methods detected performance degradation of three specific functions in comparison of two different versions of Vim, where was present a known performance issue.
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Recognition of Unique Features on Weapon Cartridges
Siblík, Jan ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
Subject of this thesis is design and implementation of an algorithm, capable of distinct feature based comparision of two weapon cartridge casing images. In the first section it looks into the issue of fi- rearms with special emphasis on ballistic traces. In following parts it presents design and imple- mentation of scanning unit for acquisition of such images and their processing and design and excuti- on of the comparation algorithm. In the conclusion there is an evaluation of goals achieved and possi- bilities for further development.
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Methods for infrared thermography with detection of specific facial areas
Kolářová, Dana ; Bernard, Vladan (referee) ; Maryšková, Věra (advisor)
This paper deals with non-contact measurement of temperature in human faces. Principle of measurement of infrared radiation and construction of the thermal imager is described in a literature search. The main part of the paper is design of an algorithm for automatic processing and the detection of regions of interest in thermal images. The theoretical description of used methods is also included in this paper. The aim is to design and implement a program for automatic evaluation of temperature changes in a human face in a sequence of thermal images that were taken with short time delay. As a part of thesis is description of implementation of designed algorithm in programming enviroment MATLAB and the description of the user interface. The program was tested on the experimental data samples. Obtained results and possible limitations are also discused in this paper.
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Automatic Transport Protocol Detection in Captured Communication
Lazárek, Zbyněk ; Kmeť, Martin (referee) ; Pluskal, Jan (advisor)
The aim of this bachelor thesis is to create a library in C#, which will be able to automatically detect transport protocols in a captured network traffic. This library can recognize a transport protocol in tunnel traffic without the knowledge of tunneling protocol. The~thesis describes the unique signatures of TCP / IP protocols on which the automatic detection is based. Furthermore, it is described how the detection works. The conclusion is~subjected to automatic detection tests, which are designed to review its performance and efficiency.
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Interpreting the learning process of an atrial fibrillation classifier
Lichtblauová, Anna ; Ředina, Richard (referee) ; Novotná, Petra (advisor)
In the theoretical part of the bachelor thesis the problems of atrial fibrillation (AF) detection and principles of convolutional neural networks (CNN) are discussed. Next, two classifiers were created in the practical part. The first was designed to classify sinus rhythm, atrial fibrillation and other pathologies, while the second further distinguished the category "atrial fibrillation" according to whether it was present in the whole recording or only in a part of it. The resulting accuracies are 82.12 \% and 85.14 \% for the first and second classifiers, respectively.
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New Models for Automatic Detection of Performance Degradation
Stupinský, Šimon ; Češka, Milan (referee) ; Rogalewicz, Adam (advisor)
Performance testing is a critical factor in the optimisation of programs during its development, but it is still not so well developed in comparison to functional testing. A framework Perun provides full automation of performance management, thereby contributing to the development of this area. We have introduced three non-parametric approaches to performance data modelling: regressogram, moving average and kernel regression, which were integrated within this framework. We try to achieve appropriate approximations of performance data using these techniques, without the assumption of dependence between two variables, which represents the main advantage in comparison to parametric techniques. Further, we have proposed and implemented two methods for automatic detection of performance changes, which works with all kinds of models within Perun . We have demonstrated our solutions on the real project ( Vim ), and on the set of the experimental cases, in which we compared proposed solutions with existing. We have achieved decreased time processing about two-thirds and an almost triple improvement in the fitness of data modelling with new modelling approaches. The proposed detection methods detected performance degradation of three specific functions in comparison of two different versions of Vim, where was present a known performance issue.
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Automatic improvements of images from 1D gel electrophoresis
Kovář, Martin ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
In this bachelor’s thesis are explained the basic principles of electrophoresis and its modalities with focusing on 1D gel electrophoresis. It describes analysis of an electrophoreogram and causes of its possible distortion, and states specifications of applications of the method in microbiology, genomics and proteomics. The practical part presents development, optimization and outputs of a programme for automatic electrophoreogram analysis, which was created in Matlab environment. The analysis contains lane and band detection and computation of samples’ molecular weight. The ending of the thesis is constituted by evaluating efficiency of detection and accuracy of weight computation.
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