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Chatbot Based on Artificial Neural Networks
Červíček, Petr ; Novotný, Ondřej (referee) ; Szőke, Igor (advisor)
The thesis pursues the implementation of the chatbot based on neural networks. It uses Long short term memory networks, which remember long-term dependencies. Chatbot was implemented in Python with superstructure Keras and is based on sequence-to-sequence. Chatbot was also tested by BLEU and given to users, who chatted with the chatbot. For a better understanding of the given problematics, there is simple description of the chatbot history and used technologies.
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Automatic sleep scoring
Schwanzer, Miroslav ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
This master thesis deals with classification of sleep stages on the base of polysomnographic signals. On several signals was performed analysis and feature extraxtion in time domain and in frequency domain as well. For feature extraxtion was used EEG, EOG and EMG signals. For classification was selected classification models K-NN, SVM and artifical neural network. Accuracy of classifation is different depending on used method and spleep stages split. The best results achieved classification among stages Wake, REM, and N3, with neural network usage. In this case the succes was 93,1 %.
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Superresulution of photography using deep neural network
Holub, Jiří ; Přinosil, Jiří (referee) ; Burget, Radim (advisor)
This diploma thesis deals with image super-resolution with conservation of good quality. Firstly, there are described state of the art methods dealing with this problem, as well as principles of neural networks with focus on convolutional ones. Finally, there is described a few models of convolutional neural network for image super-resolution to double size, which have been trained, tested and compared on newly created database with pictures of people.
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Simulation Design in Communication System Training
Takács, Endre ; Krkoš, Radko (referee) ; Škorpil, Vladislav (advisor)
The aim of this work was to analyze the problematics of modern communication systems focusing on the converged network and their elements and to propose a laboratory work. The theoretical part of the work is extensive. It deals with the network architecture OSI, which forms the basic of modern communication networks. It describes also the active network elements and their characteristics, advantages and disadvantages. The theoretical part deals in a chapter with the neuron networks, which describes the basic artificial neuron of a network, which can be used for the controlling of network elements. These networks are Hopfield network and Kohonen network. The practical part deals with the proposing of the laboratory work into the education, which is focused on the Hopfield network and the functioning of classifier switches. The work is made in Matlab.
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Football Event Recognition for Spatiotemporal Data of Gaming Objects
Čížek, Tomáš ; Bartík, Vladimír (referee) ; Rychlý, Marek (advisor)
This diploma thesis deals with automatic soccer event detection . Its goal is to introduce reader to this issue , discuss possible ways of solution of this task and then implement event detection . This work aims at event recognition using spatio - temporal data of gaming objects . Introduced way of dealing with event detection lies in its converting to sequence labeling task . Then such task is solved using LSTM recurrent neural networks . Lastly , result of sequence labeling is interpreted as detected events . Library for event detection has been created as the output of this work . This library allow user to experiment with different variants how to formulate event detection as sequence labeling task .
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Chatbot Based on Artificial Neural Networks
Červíček, Petr ; Novotný, Ondřej (referee) ; Szőke, Igor (advisor)
The thesis pursues the implementation of the chatbot based on neural networks. It uses Long short term memory networks, which remember long-term dependencies. Chatbot was implemented in Python with superstructure Keras and is based on sequence-to-sequence. Chatbot was also tested by BLEU and given to users, who chatted with the chatbot. For a better understanding of the given problematics, there is simple description of the chatbot history and used technologies.
|
|
|
Automatic sleep scoring
Schwanzer, Miroslav ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
This master thesis deals with classification of sleep stages on the base of polysomnographic signals. On several signals was performed analysis and feature extraxtion in time domain and in frequency domain as well. For feature extraxtion was used EEG, EOG and EMG signals. For classification was selected classification models K-NN, SVM and artifical neural network. Accuracy of classifation is different depending on used method and spleep stages split. The best results achieved classification among stages Wake, REM, and N3, with neural network usage. In this case the succes was 93,1 %.
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|
Football Event Recognition for Spatiotemporal Data of Gaming Objects
Čížek, Tomáš ; Bartík, Vladimír (referee) ; Rychlý, Marek (advisor)
This diploma thesis deals with automatic soccer event detection . Its goal is to introduce reader to this issue , discuss possible ways of solution of this task and then implement event detection . This work aims at event recognition using spatio - temporal data of gaming objects . Introduced way of dealing with event detection lies in its converting to sequence labeling task . Then such task is solved using LSTM recurrent neural networks . Lastly , result of sequence labeling is interpreted as detected events . Library for event detection has been created as the output of this work . This library allow user to experiment with different variants how to formulate event detection as sequence labeling task .
|
|
|
Superresulution of photography using deep neural network
Holub, Jiří ; Přinosil, Jiří (referee) ; Burget, Radim (advisor)
This diploma thesis deals with image super-resolution with conservation of good quality. Firstly, there are described state of the art methods dealing with this problem, as well as principles of neural networks with focus on convolutional ones. Finally, there is described a few models of convolutional neural network for image super-resolution to double size, which have been trained, tested and compared on newly created database with pictures of people.
|
|
|
Simulation Design in Communication System Training
Takács, Endre ; Krkoš, Radko (referee) ; Škorpil, Vladislav (advisor)
The aim of this work was to analyze the problematics of modern communication systems focusing on the converged network and their elements and to propose a laboratory work. The theoretical part of the work is extensive. It deals with the network architecture OSI, which forms the basic of modern communication networks. It describes also the active network elements and their characteristics, advantages and disadvantages. The theoretical part deals in a chapter with the neuron networks, which describes the basic artificial neuron of a network, which can be used for the controlling of network elements. These networks are Hopfield network and Kohonen network. The practical part deals with the proposing of the laboratory work into the education, which is focused on the Hopfield network and the functioning of classifier switches. The work is made in Matlab.
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