951 resultados para moving object detection


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Monitoring, object-orientation, real-time, execution-time, scheduling

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Attention, attentional blink, rapid serial visual presentation, RSVP, ERP, EEG, fMRI, gammaband, oscillatiory activity

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2011

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Ground penetrating radar; landmine; background clutter removal, buried targets detecting

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Moving grate, LEPOL, Particle, Limestone, Decomposition, Clinker, Fluidisation

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Subsurface Radar, Ground Penetrating Radar (GPR), Synthetic Aperture Radar (SAR), Anti-Personnel Landmine, Antenna Desing, Field Simulation, Focusing, Dielectric Lens, Geophysics, Soil Properties

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Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2010

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Magdeburg, Univ., Fak. für Naturwiss., Diss., 2010

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Magdeburg, Univ., Fak. für Informatik, Diss., 2013

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Ever since the appearance of the ARCH model [Engle(1982a)], an impressive array of variance specifications belonging to the same class of models has emerged [i.e. Bollerslev's (1986) GARCH; Nelson's (1990) EGARCH]. This recent domain has achieved very successful developments. Nevertheless, several empirical studies seem to show that the performance of such models is not always appropriate [Boulier(1992)]. In this paper we propose a new specification: the Quadratic Moving Average Conditional heteroskedasticity model. Its statistical properties, such as the kurtosis and the symmetry, as well as two estimators (Method of Moments and Maximum Likelihood) are studied. Two statistical tests are presented, the first one tests for homoskedasticity and the second one, discriminates between ARCH and QMACH specification. A Monte Carlo study is presented in order to illustrate some of the theoretical results. An empirical study is undertaken for the DM-US exchange rate.

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Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.

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Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength.