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Turbo codes and their applications in transmission technologies
Kuvik, Michal ; Číž, Radim (referee) ; Šilhavý, Pavel (advisor)
Purpose of this work is to clarify problems of anti-error security with the help of turbo codes. This work can be divided into two parts. In the first part we look at the theoretical aspect of features of turbo codes, their coding and at various approaches of decoding secure messages for example SOVA and MAP, also at analyzing usage of turbo codes in promising transmission technologies. Second part is focused on creating an application with the help of software Matlab and on verifying attributes of this method in this software.
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Food classification using deep neural networks
Kuvik, Michal ; Přinosil, Jiří (referee) ; Burget, Radim (advisor)
The aim of this thesis is to study problems of deep convolutional neural networks and the connected classification of images and to experiment with the architecture of particular network with the aim to get the most accurate results on the selected dataset. The thesis is divided into two parts, the first part theoretically outlines the properties and structure of neural networks and briefly introduces selected networks. The second part deals with experiments with this network, such as the impact of data augmentation, batch size and the impact of dropout layers on the accuracy of the network. Subsequently, all results are compared and discussed with the best result achieved an accuracy of 86, 44% on test data.
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Food classification using deep neural networks
Kuvik, Michal ; Přinosil, Jiří (referee) ; Burget, Radim (advisor)
The aim of this thesis is to study problems of deep convolutional neural networks and the connected classification of images and to experiment with the architecture of particular network with the aim to get the most accurate results on the selected dataset. The thesis is divided into two parts, the first part theoretically outlines the properties and structure of neural networks and briefly introduces selected networks. The second part deals with experiments with this network, such as the impact of data augmentation, batch size and the impact of dropout layers on the accuracy of the network. Subsequently, all results are compared and discussed with the best result achieved an accuracy of 86, 44% on test data.
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Turbo codes and their applications in transmission technologies
Kuvik, Michal ; Číž, Radim (referee) ; Šilhavý, Pavel (advisor)
Purpose of this work is to clarify problems of anti-error security with the help of turbo codes. This work can be divided into two parts. In the first part we look at the theoretical aspect of features of turbo codes, their coding and at various approaches of decoding secure messages for example SOVA and MAP, also at analyzing usage of turbo codes in promising transmission technologies. Second part is focused on creating an application with the help of software Matlab and on verifying attributes of this method in this software.
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