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Neural Network Number Recognition
Doupovec, Zdeněk ; Juránek, Roman (referee) ; Šilhavá, Jana (advisor)
This work describes the basic concepts and principles in the field of neural networks. Closer then deals with the problem of multilayer perceptron networks, namely back-propagation method. There are analyzed the advantages and disadvantages of these methods, the proposal of possible digits recognition system using back-propagation. The aim is to obtain concrete results from the program whitch is able to recognize numbers.
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Keyword Spotting Implementation to Mobil Phone (Symbian 60)
Cipr, Tomáš ; Schwarz, Petr (referee) ; Szőke, Igor (advisor)
Keyword spotting is one of the many applications of automatic speech recognition. Its purpose is determining spots in given utterance in which some of the specified words were spoken. Keyword spotting has a great potential to enhance performance of new applications as well as the existing ones. An example could be a mobile phone voice control. Due to OS Symbian's coming to the market it is even possible for end user to implement a keyword spotting for a mobile phone on his or her own. The thesis describes theoretical prerequisites for keyword spotting and its implementation. Firstly the OS Symbian is presented with respect to the given task. Secondly each step of keyword spotting process is described. Finally the object design of keyword spotter is presented followed by implementation description. The thesis concludes with results review and notes on possible improvements.
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Potential application of neural networks in network elements
Babnič, Patrik ; Vymazal, Michal (referee) ; Vychodil, Petr (advisor)
The goal was to get acquainted with the problems of network elements to describe neural networks that can be used to manage such a feature. The theoretical part deals with the neural networks from their inception to the present. It focuses mainly on the network, witch can be used for management control. These are the two network: Hopfield network and Kohonen network. The practical part deals with the network element model and ist implementation. It contains a practical element model using a neural network, witch is controlled by a network element.
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Elliot Wave Detection
Kaleta, Marek ; Šperka, Svatopluk (referee) ; Petřík, Patrik (advisor)
This work deals with Elliott wave detection, which are statistical tool used to describe financial makret cycles and predict market trends. The work proposes methods to detect Elliott Waves and evaluetes them. From several methods of Elliott wave detection, Committee machines of multilayer perceptrons are used. Result of this work is a program, which detect Elliott impulse waves on input signal and builds hierarchy of Elliott waves.
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Neural-Fuzzy Systems
Dalecký, Štěpán ; Samek, Jan (referee) ; Zbořil, František (advisor)
The thesis deals with artificial neural networks theory. Subsequently, fuzzy sets are being described and fuzzy logic is explained. The hybrid neuro-fuzzy system stemming from ANFIS system is designed on the basis of artificial neural networks, fuzzy sets and fuzzy logic. The upper-mentioned systems' functionality has been demonstrated on an inverted pendulum controlling problem. The three controllers have been designed for the controlling needs - the first one is on the basis of artificial neural networks, the second is a fuzzy one, and the third is based on ANFIS system. The thesis is aimed at comparing the described systems, which the controllers have been designed on the basis of, and evaluating the hybrid neuro-fuzzy system ANFIS contribution in comparison with particular theory solutions. Finally, some experiments with the systems are demonstrated and findings are assessed.
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Progressive Usage of Neural Networks in Telecommunication
Babnič, Patrik ; Kacálek, Jan (referee) ; Škorpil, Vladislav (advisor)
The main task of the Master Thesis is introduction into network elements in converget networks. Great importance is put on network elements today, that is why priority resolving is crucial. Theorethical part deals with network elements and neuron networks. Neuron networks were analysed from history to present. The main goal was to develop a neuron network topology able to manage a network element. The developed topology consists of four-layered perceptron network with four inputs and one output. The simulation was carried out on MATLAB software. No real data were used in the simulation. All input values were generated by MATLAB software hence it was a simulation.
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Real time face recognizer
Juráček, Aleš ; Přinosil, Jiří (referee) ; Richter, Miloslav (advisor)
My diploma thesis deals about face detection in picture. I try to outline problems of computer vision, artificial intelligence and machine learning. I described in details the proposed detection by Viola and Jones, which uses AdaBoost learning algorithm. This method was deliberately chosen for speed and detection accuracy. This detector was made in programming language C / C + + using the OpenCV library. To a final learning was used database of faces images „MIT CVCL Face Database“. The main goal was to propose the face detector utilizable also in video-sequences.
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Convolutional neural network for image processing
Krajčovičová, Mária ; Rajmic, Pavel (referee) ; Burget, Radim (advisor)
Goal of this Diploma thesis was Convolutional neural network investigation in last years. Diploma thesis also contains information about designing of appropriate Convolutional neural network models and implementation of these models in Java programming language. Result of the thesis are comparison and evaluation of results which were reached from implemented application.
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Recognition of digits
Gorgol, Martin ; Hynčica, Tomáš (referee) ; Jirsík, Václav (advisor)
This work describes the basic concepts and principles in the field of neural networks. Closer then this work deals with the identification numbers using these networks, in particular, using the back-propagation method. There is a broken process of choosing a set of signs, types of symptoms and of choosing a neural network topology. The aim is to obtain specific results by using the program for working with neural networks.
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Artificial Intelligence-Based Player for "Blokus" Game
Sulaiman, David ; Hrubý, Martin (referee) ; Rogalewicz, Adam (advisor)
This thesis compares forward neural networks with algorithms using game theory on basis of board game Blokus. The theoretical introduction part describes the characteristics of neural networks and work with them. There is also outlined algorithm of game theory. The second part deals about the implementation of players based on the outlined principles and shortly descriptions GUI of application. In conclusion, the differences between the players are evaluated on the charts created on the performed tests.
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