Titlebook: Systemwechsel und Demokratisierung; Rußland und Mittel-O Gert-Joachim Glaeßner,Michal Reiman Textbook 1997 Westdeutscher Verlag GmbH, Oplad

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rmed a simulated trauma resuscitation two times while wearing Xsens. MTw motion trackers to track head movements during the resuscitation. These motions were analyzed using a standard measure of discriminating movement patterns known as the Hurst exponent (.). Pre- and post- communication training m

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Michal Reiman sufficient to offset the small additional cost of a sensing system, and that such systems will become common in the near future. Table of Contents: Introductio978-3-031-01369-0978-3-031-02497-9Series ISSN 1931-9525 Series E-ISSN 1931-9533

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Gert-Joachim Glaeßner,Michal Reimanigned for a professional audience composedofpractitionersandresearchersinindustry.Thisvolumeisalsosu- able as a reference or secondary text for advanced-level students in computer science and engineering. The c978-1-4419-4442-9978-0-387-72500-0Series ISSN 1568-2358 Series E-ISSN 2945-5715

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tations of one-dimensional signals, such as the spectrogram. Specifically, we use the PDE model introduced by ´ Alvarez, Lions and Morel for noise smoothing and edge enhancement, which we show to be stable under signal and window perturbations in the spectrogram image. We demonstrate by numerical ex

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Gert-Joachim Glaeßner,Michal Reimanc of securing image information.Includes supplementary materTraditionally,signalprocessingtechniqueslayatthefoundationofmultimedia data processing and analysis. In the past few years, a new wave of advanced signal-processing techniques has delivered exciting results, increasing systems capabilities

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Gert-Joachim Glaeßnernal-processing techniques has delivered exciting results, increasing systems capabilities of e?ciently exchanging image data and extracting useful kno- edge from them. Signal Processing for Image Enhancement and Multimedia Processing is an edited volume, written by well-recognized international - se

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Leonid A. Gordonxtremely time-consuming. This paper focuses on reducing the computational cost in order to process large document images. We introduce thus a local-global Mean Shift based color image segmentation approach. It is a two-steps procedure carried out by updating and propagating cluster parameters using

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