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Program for evaluating image quality using neural network
Šimíček, Pavel ; Kratochvíl, Tomáš (referee) ; Slanina, Martin (advisor)
This thesis studies the assessment of picture quality using the artificial neural network approach. In the first part, two main ways to evaluate the picture quality are described. It is the subjective assessment of picture quality, where a group of people watches the picture and evaluates its quality, and objective assessment which is based on mathematical relations. Calculation of structural similarity index (SSIM) is analyzed in detail. In the second part, the basis of neural networks is described. A neural network was created in Matlab, designed to simulate subjective assessment scores based on the SSIM index.
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Simulating the control of a network element with neural network
Šilhan, Petr ; Kacálek, Jan (referee) ; Škorpil, Vladislav (advisor)
The thesis deals with the use of neuronal networks for the control of telecommunication network elements. The aim of the thesis is to create a simulation model of network element with switching array with central memory, in which the optimization control switching array is solved by means of the Hopfield neural network. All source code is created in integrated environment MATLAB with the use of Neural Network Toolbox.
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Implementation of quality of service in the control of a network element
Boháč, Martin ; Kyselák, Martin (referee) ; Škorpil, Vladislav (advisor)
The main task of the Master Thesis is introduction into problems of quality of service in converged networks especially with use of IP protocol version 6. Converged networks are able to transfer different data types - voice, data or multimedia stream. Design of active network unit is realized in Matlab Simulink. Designed model consists of simple network with some computer terminals which are connected with network element - switch. Switch model simulates real traffic of computer terminals, that are sending data to remote users. Packets in switch are sorting by data stream type and QoS. Switch is managed by neuron network. Neuron network reacts to input data and controls switch depending on type of recipient. Switch model can be used in laboratory exercising. Solving this theme needs basic skill in Simulink and theme can be done in one laboratory exercise.
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Adaptive data compression by neural networks
Kučera, Michal ; Přinosil, Jiří (referee) ; Koula, Ivan (advisor)
Point of the work is using of neural networks for the datecompression. This brings new possibilities as by lossless as lossy compression. Draft of a few compress algorithm show the behaviour, advantages and weak points of these systems. As the solution we use knowledge of the layered perceptron Network and we try by the change of the structure and subparameters to teach such network to compress the data, according to our entry requirement. These networks have also advantages, which are meanwhile impediment to the using practically. The goal of this is to try some algorithms, look into their characteristics and posibility of the using. Then propose next posibility solutions and upgrading of these algorithms.
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Application of neural networks in telecommunications
Šulák, Michal ; Koula, Ivan (referee) ; Kacálek, Jan (advisor)
This Master’s Thesis consists of description of current routing protocols and routers, basic principles of neural networks and their interpretation in connection with the use for routing in data networks and telecommunications networks. In the thesis I focused on neural networks, which use energetic functions to find solution stabled states and their use for data routing. I produced the application software to test and find suitable variables for each function. This application counts the shortest path and is able to change variables to reach the best solution of stabled state of neural network. These solutions are compared with other functions that are usually used in nowadays systems for data network routing.
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Detection of speech disorders
Struhař, Michal ; Rajmic, Pavel (referee) ; Sysel, Petr (advisor)
This thesis deals with detection of speech disorders. One of the aims of this thesis is choosing suitable parameterization: short-time energy, zero-crossing rate, linear predictive analysis, perceptual linear predictive analysis, RASTA method, cepstral analysis and mel-frequency cepstral coefficient can be chosed for detections. Next aim is construction of detector of speech disorders based on DTW (Dynamic Time Warping) and artificial neuron network. Single detection proceeds on the base of collected tokens from chosen analysis and phonetic transcription of speech. Analyses, detector and phonetic transcription of Czech language are implemented in simulation environment of MATLAB.
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Picture symbol identification with the aid of neural network
Pavlík, Daniel ; Burget, Radim (referee) ; Kohoutek, Michal (advisor)
This thesis is about using neural networks in recognition of letters A to Z and numbers 0 to 9. In the first part is theoretically described substance of neural networks and concretically described principle the method of learning multiple-layer network with backward spreaded error(a.ka Backpropagation). Basic problematic of processing the picture and resilence of network against degradation picture by a noise and compression JPEG is also described here. Second part is directed to practical realization of feed foward multiple-layer network with recognition the binary patterns of alphabetical letters and numbers 0 to 9, which was created in Matlab and Simulink environment. Next and final part is about practical realization of feed foward network with recognition the grayscale patterns of alphabetical letters and numbers 0 to 9, which was also created in Matlab and Simulink environment.
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Detection of Object
Šenkýř, Ivo ; Richter, Miloslav (referee) ; Jirsík, Václav (advisor)
This diploma thesis deals with a problem of spores venturia inaequlis recognition. These spores are captured on a special tape which is then analyzed using a microscope. The tape can be analyzed by a laboratorian or by the program Sporedetect v3. This program provides functions for complete picture processing and object recognition. In this diploma thesis, there are also described ways to automatically control a sliding stage of a microscope utilizing motorized translation stages and linear actuators. The information about automatic control of a microscope stage was obtained from catalogues of the companies Standa and Edmundoptics.
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Predictive Analytics - Process and Development of Predictive Models
Praus, Ondřej ; Pour, Jan (advisor) ; Mrázek, Luboš (referee)
This master's degree thesis focuses on predictive analytics. This type of analysis uses historical data and predictive models to predict future phenomenon. The main goal of this thesis is to describe predictive analytics and its process from theoretical as well as practical point of view. Secondary goal is to implement project of predictive analytics in an important insurance company operating in the Czech market and to improve the current state of detection of fraudulent insurance claims. Thesis is divided into theoretical and practical part. The process of predictive analytics and selected types of predictive models are described in the theoretical part of the thesis. Practical part describes the implementation of predictive analytics in a company. First described are techniques of data organization used in datamart development. Predictive models are then implemented based on the data from the prepared datamart. Thesis includes examples and problems with their solutions. The main contribution of this thesis is the detailed description of the project implementation. The field of the predictive analytics is better understandable thanks to the level of detail. Another contribution of successfully implemented predictive analytics is the improvement of the detection of fraudulent insurance claims.
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