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Optical processing of questionnaires
Nožka, Tomáš ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
This master thesis deals with the principles of form design, form printing and form processing. Three different types of forms and applications for their detection are created with the reference of these principles. This application provides to create a new type of form and to print out a form. The application itself is implemented in C++ with the use of OpenCV library. This work describes the classification methods of direction finding marks, identification numbers and submission numbers, bar codes EAN-13, page numbers, answer fields and single answers. The classification of all the handwritten numbers is implemented by neural nets.
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Optimization of Voice Recognition for Mobile Devices
Tomec, Martin ; Zbořil, František (referee) ; Hanáček, Petr (advisor)
This work deals with optimization of keyword spotting algorithms on processor architecture ARM Cortex-A8. At first it describes this architecture and especially the NEON unit for vector computing. In addition it briefly describes keyword spotting algorithms and also there is proposed optimization of these algorithms for described architecture. Main part of this work is implementation of these optimizations and analysis of their impact on performance.
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Protein Classification Techniques
Dekrét, Lukáš ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
Main goal of classifying proteins into families is to understand structural, functional and evolutionary relationships between individual proteins, which are not easily deducible from available data. Since the structure and function of proteins are closely related, determination of function is mainly based on structural properties, that can be obtained relatively easily with current resources. Protein classification is also used in development of special medicines, in the diagnosis of clinical diseases or in personalized healthcare, which means a lot of investment in it. I created a new hierarchical tool for protein classification that achieves better results than some existing solutions. The implementation of the tool was preceded by acquaintance with the properties of proteins, examination of existing classification approaches, creation of an extensive data set, realizing experiments and selection of the final classifiers of the hierarchical tool.
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Smart Interaction of Robot with Human
Nováčik, Tomáš ; Rozman, Jaroslav (referee) ; Luža, Radim (advisor)
This bachelor thesis investigates the usage of neural networks and their applications on the problem of smart home. Used localization system is based on WLAN technology. For activities rocognition is used LSTM recurrent neural network. For simulation purposes is used robot operating system.
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Protein Classification Techniques
Dekrét, Lukáš ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
Main goal of classifying proteins into families is to understand structural, functional and evolutionary relationships between individual proteins, which are not easily deducible from available data. Since the structure and function of proteins are closely related, determination of function is mainly based on structural properties, that can be obtained relatively easily with current resources. Protein classification is also used in development of special medicines, in the diagnosis of clinical diseases or in personalized healthcare, which means a lot of investment in it. I created a new hierarchical tool for protein classification that achieves better results than some existing solutions. The implementation of the tool was preceded by acquaintance with the properties of proteins, examination of existing classification approaches, creation of an extensive data set, realizing experiments and selection of the final classifiers of the hierarchical tool.
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Detection of snow avalanche debris from satellite synthetic aperture radar (SAR) data
Klímová, Tereza ; Kolář, Jan (advisor) ; Brodský, Lukáš (referee)
DETECTION OF SNOW AVALANCHE DEBRIS FROM SATELLITE SYNTHETIC APERTURE RADAR (SAR) DATA Abstract This thesis engages with detection of snow avalanche debris at radar images taken with synthetic aperture radar on Sentinel-1 satellite. The aim is to find method for recognizing places at image where is the snow avalanche debris. A method is based on neural net principle, specifically on using pre-trained model of neural net VGG-19. According to results of neural net, training images are splitted into two cathegories: there is an avalanche and there is not. It is called binary classification. The result is statistical evaluation of success rate compared with other traditional methods. keywords: snow avalanche, Sentinel-1, neural net, VGG-19
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Smart Interaction of Robot with Human
Nováčik, Tomáš ; Rozman, Jaroslav (referee) ; Luža, Radim (advisor)
This bachelor thesis investigates the usage of neural networks and their applications on the problem of smart home. Used localization system is based on WLAN technology. For activities rocognition is used LSTM recurrent neural network. For simulation purposes is used robot operating system.
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Optimization of Voice Recognition for Mobile Devices
Tomec, Martin ; Zbořil, František (referee) ; Hanáček, Petr (advisor)
This work deals with optimization of keyword spotting algorithms on processor architecture ARM Cortex-A8. At first it describes this architecture and especially the NEON unit for vector computing. In addition it briefly describes keyword spotting algorithms and also there is proposed optimization of these algorithms for described architecture. Main part of this work is implementation of these optimizations and analysis of their impact on performance.
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