Browsing by Subject "Machine Learning"

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  • Schäfer, Marlin Benedikt (Hannover : Gottfried Wilhelm Leibniz Universität, 2019)
    Gravitational waves are now observed routinely. Therefore, data analysis has to keep up with ever improving detectors. One relatively new tool to search for gravitational wave signals in detector data are machine learning ...
  • Vogt, Karsten (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2019)
    Diese Arbeit beschäftigt sich mit dem Problem der semantischen Segmentierung von Luftbildern in Landbedeckungsklassen. Maschinelle Lernverfahren bieten dabei sehr robuste Methoden zur Erzeugung von hochgenauen Klassifikatoren, ...
  • Diem, Michael; Braun, Anja; Louw, Louis (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2020)
    Rising consumption due to a growing world population and increasing prosperity, combined with a linear economic system have led to a sharp increase in garbage collection, general pollution of the environment and the threat ...
  • Khangura, Sukhpreet Kaur (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2019)
    Today’s Internet Protocol (IP), the Internet’s network-layer protocol, provides a best-effort service to all users without any guaranteed bandwidth. However, for certain applications that have stringent network performance ...
  • Samsonov, Vladimir; Enslin, Christmarie; Lütkehoff, Ben; Steinlein, Felix; Lütticke, Daniel; Stich, Volker (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2020)
    Changing customer demands lead to increasing product varieties and decreasing delivery times, which in turn pose great challenges for production companies. Combined with high market volatility, they lead to increasingly ...
  • Brede, Sebastian; Küster, Benjamin; Stonis, Malte; Mücke, Mike; Overmeyer, Ludger (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2020)
    The dominating mass-manufacturing process of today is plastic injection molding. This production process uses economies of scale because parts are produced in seconds at marginal cost of plastics. However, upfront investment ...
  • Denkena, Berend; Dittrich, Marc-André; Uhlich, Florian (Amsterdam : Elsevier, 2016)
    The continuous integration of manufacturing systems and sensory components leads to an increasing amount of available process data. In addition, new database systems and the parallelization of data processing enable to ...
  • Tsiapoki, Stavroula (Hannover : Institut für Statik und Dynamik, Leibniz Universität Hannover, 2018)
    Over the past forty years, intensive research has been carried out in the field of structural health monitoring (SHM), since the identification of damage at an early stage contributes to avoiding structural failure and ...
  • Krause, Anna (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2019)
    AGIAS Generalised Interval Arithmetic Simulator (AGIAS) is a specialised simulator which uses affine arithmetic to model parameter variations. It uses a specialised root-finding algorithm to simulate analogue circuits ...