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1–10 von 178 Ergebnissen
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    XGBoost Gradient-Boosted Tree Predictions Using Limited Data for Coaxial Rotor Helicopters

    Seidel, Cory A. / Genter, Ethan / Peters, David A. | AIAA | 2021
    Schlagwörter: Reinforcement Learning

    Visual recognition of hexagonal headed bolts by comparing ICA to wavelets

    Mazzeo, P.L. / Ancona, N. / Stella, E. et al. | Tema Archiv | 2003
    Schlagwörter: Lernen

    Vibration modeling improves pipeline performance, costs

    Ben Rahmoune Mohamed / Hafaifa, Ahmed / Mouloud, Guemana | Tema Archiv | 2015
    Schlagwörter: Lernprozess

    Verification of Image-Based Neural Network Controllers Using Generative Models

    Katz, Sydney M. / Corso, Anthony L. / Strong, Christopher A. et al. | AIAA | 2022
    Schlagwörter: Machine Learning

    UUV teams, control from a biological perspective

    McDowell, P. / Chen, J. / Bourgeois, B. | Tema Archiv | 2002
    Schlagwörter: Lernen , maschinelles Lernen

    Utilizing Reinforcement Learning to Continuously Improve a Primitive-Based Motion Planner

    Goddard, Zachary C. / Wardlaw, Kenneth / Williams, Kyle et al. | AIAA | 2022
    Schlagwörter: Reinforcement Learning

    Using Visualization of Convolutional Neural Networks in Virtual Reality for Machine Learning Newcomers

    Freier Zugriff
    Meissler, Nadine / Wohlan, Annika / Hochgeschwender, Nico et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2019
    Schlagwörter: knowledge learning

    Using Deep Learning to Predict Unstable Approaches for General Aviation Aircraft

    Jain, Tanish / Misra, Shlok / Truong, Dothang | AIAA | 2022
    Schlagwörter: Machine Learning

    Unsupervised prototype reduction for data exploration and an application to air traffic management initiatives

    Estes, Alexander / Lovell, David J. / Ball, Michael O. | Online Contents | 2019
    Schlagwörter: Unsupervised learning

    Two-Phase Neural Combinatorial Optimization with Reinforcement Learning for Agile Satellite Scheduling

    Zhao, Xuexuan / Wang, Zhaokui / Zheng, Gangtie | AIAA | 2020
    Schlagwörter: Reinforcement Learning