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Object Recognition by Neural Networks
Marák, Jaroslav ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This thesis is focused on neural networks and their classification capability in object recognition tasks. For recognition is there used neural networks with feedforward architecture which is learned by Back Propagation algorithm. We discusses about problems which appear while a choosing topology of network or using various lerning-significant parametters while a learning process. Achieved results are presented in experiments with estimation.
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Neural Network Based Edge Detection
Jamborová, Soňa ; Grézl, František (referee) ; Švub, Miroslav (advisor)
This work is about suggestion and implementation of the software for detection of edges in images using neurons network. It defines basic terms for this topic and focusing mainly at preperation imaging imformation for detection using nerons network. Describing and comparing different aproachings for using implemented software on synthetic and real set of images, including experiments.
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Optimization of Active Network Element Control
Přecechtěl, Roman ; 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 memory, in which the optimization kontrol switching array is solved by means of the neural network. All source code is created in integrated environment MATLAB. To training are used feed-forward backpropagation network. Miss achieve satisfactory result mistakes. Work apposite decision procedure given to problem and it is possible on ni tie up in an effort to find optimum solving.
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Object Recognition by Neural Networks
Marák, Jaroslav ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This thesis is focused on neural networks and their classification capability in object recognition tasks. For recognition is there used neural networks with feedforward architecture which is learned by Back Propagation algorithm. We discusses about problems which appear while a choosing topology of network or using various lerning-significant parametters while a learning process. Achieved results are presented in experiments with estimation.
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|
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Neural Network Based Edge Detection
Jamborová, Soňa ; Grézl, František (referee) ; Švub, Miroslav (advisor)
This work is about suggestion and implementation of the software for detection of edges in images using neurons network. It defines basic terms for this topic and focusing mainly at preperation imaging imformation for detection using nerons network. Describing and comparing different aproachings for using implemented software on synthetic and real set of images, including experiments.
|
|
|
Optimization of Active Network Element Control
Přecechtěl, Roman ; 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 memory, in which the optimization kontrol switching array is solved by means of the neural network. All source code is created in integrated environment MATLAB. To training are used feed-forward backpropagation network. Miss achieve satisfactory result mistakes. Work apposite decision procedure given to problem and it is possible on ni tie up in an effort to find optimum solving.
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