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Reliable visual systems
Honec, Peter ; Janáková, Ilona (advisor)
The Doctoral thesis demonstrates the design of reliable industrial visual systems. The special emphasis is dedicated to the detection of defects on webs in industrial applications based on line-scan cameras. This system makes possible detection and classification of defects originating during the real production conditions. This work covers a theoretical study of a visual system for the defect detection on endless bands as well as of appropriate lighting and the scene arrangement. Further to that have been selected, adjusted and designed key components of hardware. Following the design and optimization of algorithms a system prototype had been installed on non-woven textiles production line. Eight visual systems implemented into real-life industrial conditions based on this prototype
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PHONOTACTIC AND ACOUSTIC LANGUAGE RECOGNITION
Matějka, Pavel ; Sigmund, Milan (advisor)
Práce pojednává o fonotaktickém a akustickém přístupu pro automatické rozpoznávání jazyka. První část práce pojednává o fonotaktickém přístupu založeném na výskytu fonémových sekvenci v řeči. Nejdříve je prezentován popis vývoje fonémového rozpoznávače jako techniky pro přepis řeči do sekvence smysluplných symbolů. Hlavní důraz je kladen na dobré natrénování fonémového rozpoznávače a kombinaci výsledků z několika fonémových rozpoznávačů trénovaných na různých jazycích (Paralelní fonémové rozpoznávání následované jazykovými modely (PPRLM)). Práce také pojednává o nové technice anti-modely v PPRLM a studuje použití fonémových grafů místo nejlepšího přepisu. Na závěr práce jsou porovnány dva přístupy modelování výstupu fonémového rozpoznávače -- standardní n-gramové jazykové modely a binární rozhodovací stromy. Hlavní přínos v akustickém přístupu je diskriminativní modelování cílových modelů jazyků a první experimenty s kombinací diskriminativního trénování a na příznacích, kde byl odstraněn vliv kanálu. Práce dále zkoumá různé druhy technik fúzi akustického a fonotaktického přístupu. Všechny experimenty jsou provedeny na standardních datech z NIST evaluaci konané v letech 2003, 2005 a 2007, takže jsou přímo porovnatelné s výsledky ostatních skupin zabývajících se automatickým rozpoznáváním jazyka. S fúzí uvedených technik jsme posunuli state-of-the-art výsledky a dosáhli vynikajících výsledků ve dvou NIST evaluacích.
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Modern methods of QRS detection
Fajkus, Jiří ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
This bachelor’s thesis deals with methods, which are used for processing of ECG signals, specifically for the detection of QRS complexes. The QRS detection is an essential part of every ECG analysis because it is a source of points with timing information, which are used for classification and measurement of other waves and intervals required for diagnostics. Some ways of QRS detection are described in this work and there is also a description of detector implemented in programming environment MATLAB, which is based on zero crossing counts. This QRS detector was then tested CSE database and signals from Holter examination.
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The Risk of Selection of Supplier
Pokorná, Klára ; Kučeríková, Michaela (referee) ; Dostál, Petr (advisor)
The Master’s thesis deals with the area of supplier management in a large multinational corporation focused on manufacturing and distribution of medical devices, which has a subsidiary in the Czech Republic. The thesis discusses the analysis of the current set up of supplier management in the facility and there are calculations for effective evaluation of suppliers being proposed on the basis of the analysis. The emphasis is also put on the setting of the system such that it provides the highest possible added value for its users, can be easily implemented in practice and is flexible as well.
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Evaluation of Flood Waves in the Upper Part of Jihlava River Basin
Kozel, Tomáš ; Marton, Daniel (referee) ; Starý, Miloš (advisor)
This thesis is about construction of forecasting models for prediction of flood flows of systems measuring profile Batelov – Dvorce, Dvorce – Ptáčov and Batelov – Ptáčov on the river Jihlava. For forecasting flood flows were used classic hydrological forecasting models. Another forecasting models contained neural networks. Data for construction of forecasting models were used for years 1960 – 2010. Evaluation was made in the end of thesis. The thesis also containes theoretical line of flood flows volume.
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Flood Prediction in Borovnice - Dalečín Measure Profiles
Hiesböcková, Tereza ; Janál, Petr (referee) ; Starý, Miloš (advisor)
Aim of a work is construction of forecasting models for prediction of flood flows of measuring profile Borovnice – Dalečín on the river Svratka. As a tool for issuing predictions will be used classic hydrological forecasting models, and models based on artificial intelligence methods. Predictive model will be consisting from summer flood flows for the years 1997-2007. In the end of the work will chosen a better method for issuing forecasts
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Analysis and Prediction of Foreign Exchange Markets by Chaotic Attractors and Neural Networks
Pekárek, Jan ; Dostál, Petr (referee) ; Budík, Jan (advisor)
This thesis deals with a complex analysis and prediction of foreign exchange markets. It uses advanced artificial intelligence methods, namely neural networks and chaos theory. It introduces unconventional approaches and methods of each of these areas, compares them and uses on a real problem. The core of this thesis is a comparison of several prediction models based on completely different principles and underlying theories. The outcome is then a selection of the most appropriate prediction model called NAR + H. The model is evaluated according to several criteria, the pros and cons are discussed and approximate expected profitability and risk are calculated. All analytical, prediction and partial algorithms are implemented in Matlab development environment and form a unified library of all used functions and scripts. It also may be considered as a secondary main outcome of the thesis.
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The Use of Artificial Intelligence on Stock Market
Barjak, Maroš ; Budík, Jan (referee) ; Dostál, Petr (advisor)
The thesis deals with design, implementation and optimization of a model based on artificial intelligence and neural networks, which is able to predict future time series prices on a stock market. Main goal is to create an object oriented application for successful future trend prediction of financial derivatives with the use of cooperating methods such as Hurst exponent evaluation and automated market simulation.
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