National Repository of Grey Literature 65 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Automatic detection of ischemia in ECG
Noremberczyk, Adam ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) for detection of coronary artery disease (CAD) in frequency area. The first part of this thesis is orientated towards the theoretical knowledge. Describes the issue of ECG pathological changes. ECQ are converted to frequency area. Described statistical methods and methods for automatic detection of CAD and MI. Explained the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB®. This part focuses on counting and finding suitable parameters and making connection of band. At the end of the thesis UNS is used to detect ischemic parameters and the results are discussed. Average values for the best settings are 100% accuracy.
Competitions in Artificial Intelligence
Šafář, Pavel ; Hynčica, Tomáš (referee) ; Honzík, Petr (advisor)
My thesis is focused on the field of artificial intelligence and especially on the competitions in the areas of robotics, computer vision, communication, time series forecasting and game playing programmes. Furthermore I devoted myself to the research of the use of neural network as a tool to solve the Gomoku game problems. The neural network processes the game situations and sets up the output values based on the pre-set models.
The use of artificial intelligence in cryptography
Lavický, Vojtěch ; Rosenberg, Martin (referee) ; Babnič, Patrik (advisor)
Goal of this thesis is to get familiar with problematics of neural networks and commonly used security protocols in cryptography. Theoretical part of the thesis is about neural networks theory and chooses best suitable type of neural network to use in cryptographic model. In practical part, a new type of security protocol is created, using chosen neural network.
Comparison of Classification Methods
Dočekal, Martin ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
Demonstrational Program for IZU Course
Míšová, Miroslava ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This bachelor's thesis deals with development of new study aplications for course Fundamentals of Artificial Intelligence. These aplications are based on the older version of JavaApplet, which use features, that are no longer supported. Each applicatoin was made acording to an object-oriented paradigm and than implemented. Special care was taken in order for the UI to be intuitive and easy to use and also for the aplication to be able to be further developed.
Classification of ECG by artificial neural networks
Loviška, David ; Vítek, Martin (referee) ; Hrubeš, Jan (advisor)
The aim of project with name Classification ECG by artificial neural networks is simplify and speed up working a doctor. That reaches created program that the is capable simply and almost at once classify EKG signal using artificial neuronal nets. Created program will give to the doctor basic information about used electrocardiogram, as are time period and amplitude signal in single surveyed sections. Subsequently will program warn doctor about abnormalities from normal. Part of program is also graphic window with painted signal and on him in color points and partitions marked by program behind special. In next phase program alone classifies gained data and designating without doctor diagnose that doctor can evaluate and in case agreeable it sign and place for true diagnose patient. This program is also fit for data reading from bigger of the number of hours as far as days. It is concerned primarily Holter ECG monitoring.
Neural network implementation into microcontroler
Čermák, Justin ; Vávra, Jiří (referee) ; Bohrn, Marek (advisor)
This bachelor thesis handles about implementation of multi layer neural networks for character recognition into the PC and microcontrollers. The practical part describes how to design and implement a simple program for pattern recognition of numbers using multi layer neural networks.
Usage of the MATLAB environment for neural networks
Lenk, Peter ; Atassi, Hicham (referee) ; Škorpil, Vladislav (advisor)
This bachelor thesis discusses the basic theory and modelling of neural networks in the software environment of MATLAB. The thesis can be divided into four parts. After an introduction into the thesis, the theoretical background of the neural netwoks is explained in the first chapter. This chapter features a brief history and a biological background of neural networks and deals with the basic network architectures and the training processes. The next part is the description of how to implement networks in a general way using the MATLAB enviroment, so it deals with preparation of data, creation, simulation and training of a neural network. The last part of the paper covers a design of two excersises created in order to introduce modelling of the neural networks in the MATLAB enviroment to the students.
Cell segmentation using convolutional neural networks
Hrdličková, Alžběta ; Chmelík, Jiří (referee) ; Vičar, Tomáš (advisor)
This work examines the use of convolutional neural networks with a focus on semantic and instance segmentation of cells from microscopic images. The theoretical part contains a description of deep neural networks and a summary of widely used convolutional architectures for image segmentation. The practical part of the work is devoted to the creation of a convolutional neural network model based on the U-Net architecture. It also contains cell segmentation of predicted images using three methods, namely thresholding, the watershed and the random walker.
Application of Neural Networks for Human Face Localization
Žák, Jakub ; Štancl, Vít (referee) ; Švub, Miroslav (advisor)
This paper describes aplication of multi layered neural network for solving problem of detection human face in static picture. This Method has good generalizational capabilities in general and there is no need to assembly complex models of analyzed data. There is also mentioned posibility of using neural network with changed architecture in this work.

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