Detection and Classification of Military Targets in a Videosignal

Cílem této práce je návrh a implementace vhodných algoritmů na detekci a klasifikaci vzdálených cílů. Čtenář bude seznámen s dvojicí algoritmů pro detekci pohybu. Jedná se o odčítání dvou po sobě jdoucích snímků a o komplexnější algoritmus, který je založený na Bayesovském klasifikátoru. Dále mu budou představeny dva možné způsoby klasifikace, konkrétně pomocí support vector machines a pomocí množiny lineárních klasifikátorů. V závěru práce budou dané algoritmy zhodnoceny.The aim of this thesis is to design and implement algorithms for detection and classification of distant targets. The reader will become familiar with algorithms for detection of a movement, namely image difeerentiation and an algorithm based on a Bayes classifier. In the following two possible ways of classification, one using support vector machines and the second one utilizing a set of linear classifiers, will be introduced. At the end of this thesis results of the algorithms will be described and evaluated.

Augmented Reality for Training and Execution of Airplane Maintenance

Tato práce se zabíva rozšířenou realitou a jejím použitím při vykonávání údžby letadel. Její součastí je take rozsáhle studium problemaky rozšířene reality, leteckých servisních procedur a předchádzejících pokusů o jejich spojení. Dále bylo v rámci teto práce natočených několik servisních procedur a vytvořena aplikace, která byla na nich otestováná. Výsledky těchto testů spolu s návrhem dalších vylepšení je možné najít prímo v práci.This thesis deals wtih augmented reality applied to aircraft maintenance which is widely explored here. Furthermore, a reseach is done on the previous work done in this field. A video data-set is acquired from LET - a manufacturer of LET L-410 aircraft and an application is created in order to test possibilities of using augmented reality in aircraft maintenance. The result and proposals of the future work can be found in this thesis as well

Theoretical evaluation of bifurcation in dependence on resonance frequency in two-coil inductive power transfer

Operation of two-coil inductive power transfer (IPX) system is affected by bifurcation phenomenon. In this paper, bifurcation in dependency on resonance frequency is examined. At first, voltage equations are analyzed, and impedance and transfer function derived. In next step, condition for resonance frequency is stated, which is followed by bifurcation analysis. Resulting bifurcation map is analytically described. Lastly, impacts of bifurcation on resonance frequency choice are evaluated using impedance and transfer function

Novel Method of Coupling Coefficient Estimation Based on the Bifurcation Phenomena in Inductive Power Transfer

Inductive power transfer (IPT) applications, such as stationary charging of electric vehicles (EVs), at least moderate coupling between the coils to achieve high efficiency, but the coefficient k typically varies between of 0.1 to 0.4, depending on the displacement of the coils according to SAE J2954. Thus, accurate and reliable methods for estimation of k are required for positioning of the EV to achieve optimal alignment with the charging pad. Additionally, in IPT, numerous control strategies are available for regulating output power and optimizing system efficiency that require an accurate estimate of the mutual inductance or k. However, existing estimation methods tend to require detailed a-priori information of a large number of circuit parameters, or they need measurement of currents or voltages in both primary and secondary sides. This paper presents a preliminary evaluation of a novel, primary-side method to estimate k, which is based solely on the frequency response of the input phase while operating the system in bifurcation. The method does not require any additional measurements of the system parameters. The theoretical background of the method is presented together with the description of the measurement procedure. The method is experimentally verified and compared with two currently used estimation methods. According to the presented experimental evaluation, the proposed method estimates k with an error of 3.62% with respect to the reference over the evaluated range of 0.08 to 0.36. In addition, we demonstrate that the presented method is resilient to detuning