TY - JOUR A1 - Hüning, Felix A1 - Luken, Heiko A1 - Schilder, Herbert A1 - Eifert, Thomas T1 - Magnetochemistry: Compounds and Concepts / Lueken, Heiko ; Schilder, Herbert ; Eifert, Thomas ; Handrick, Klaus ; Hüning, Felix JF - Advances in Solid State Physics. 201 (2001) Y1 - 2001 SP - 515 EP - 532 PB - - ER - TY - PAT A1 - Engels, Elmar T1 - Magnetlesekopf, Magnetspeicherleseeinrichtung und Verfahren zum abgesicherten Auslesen und Verarbeiten von magnetisch gespeicherten Daten : Offenlegungsschrift : DE102006049162A1 ; Offenlegungstag: 24.04.2008 Y1 - 2008 N1 - Volltext über Datenbank: http://publikationen.dpma.de/ PB - Deutsches Patent- und Markenamt CY - München ER - TY - BOOK A1 - Hüning, Felix T1 - Magnetische Eigenschaften niederdimensionaler Chrom-, Ruthenium- und Niobhalogenide Y1 - 2001 SN - 3-8265-8551-8 N1 - zugl.: Techn. Hochsch., Diss. Aachen 2000 PB - Shaker CY - Aachen ER - TY - JOUR A1 - Schmitt, Robert A1 - Scholl, Ingrid A1 - Cai, Yu A1 - Xia, Ji A1 - Dziwoki, Paul A1 - Harding, Martin A1 - Pavim, Alberto T1 - Machine Vision System for Inline Inspection in Carbide Insert Production JF - Bildverarbeitung für die Medizin 2010 : Algorithmen, Systeme, Anwendungen ; Proceedings des Workshops vom 14. bis 16. März in Aachen / Thomas M. Deserno ... (Hrsg.) Y1 - 2010 SN - 978-3-642-11967-5 N1 - Proceedings of the 36th International MATADOR Conference ; Workshop Bildverarbeitung für die Medizin <2010, Aachen> SP - 339 EP - 342 PB - Springer CY - Berlin ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Elsen, Ingo A1 - Schiffer, Stefan T1 - Machine learning based 3D object detection for navigation in unstructured environments T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) N2 - In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine. KW - 3D object detection KW - LiDAR KW - autonomous driving KW - Deep learning KW - Three-dimensional displays Y1 - 2021 SN - 978-1-6654-7921-9 U6 - http://dx.doi.org/10.1109/IVWorkshops54471.2021.9669218 N1 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021, Nagoya, Japan. SP - 236 EP - 242 PB - IEEE ER - TY - CHAP A1 - Stenger, David A1 - Altherr, Lena A1 - Abel, Dirk T1 - Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead T2 - Operations Research Proceedings 2018 N2 - In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead. KW - Product family optimization KW - Mixed-integer nonlinear black-box optimization KW - Engineering optimization KW - Machine learning Y1 - 2019 SN - 978-3-030-18499-5 (Print) SN - 978-3-030-18500-8 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-18500-8_47 SP - 379 EP - 385 PB - Springer CY - Cham ER - TY - JOUR A1 - Heuermann, Holger T1 - LZY: A Self-Calibration Approach in Competition to the LRM Method for On-Wafer Measurements Y1 - 1995 N1 - 45th ARFTG Conference digest, Spring 1995 : [conference topic: Testing and design of RFIC'S], May 19, 1995, Orange County Convention Center, Orlando, Florida / Automatic RF Techniques Group. Publications chairman: Ed Godshalk; ARFTG Conference digest ; 4 SP - 129 EP - 136 ER - TY - JOUR A1 - Sommer, Angela M. A1 - Bitz, Andreas A1 - Streckert, Joachim A1 - Hansen, Volkert W. A1 - Lerchl, Alexander T1 - Lymphoma development in mice chronically exposed to UMTS-modulated radiofrequency electromagnetic fields JF - Radiation Research Y1 - 2007 U6 - http://dx.doi.org/10.1667/RR0857.1 SN - 1938-5404 VL - 168 IS - 1 SP - 72 EP - 80 ER - TY - JOUR A1 - Hagemann, Hans-Jürgen T1 - Loss mechanisms and domain stabilization in doped BaTiO₃ JF - Journal of Physics C: Solid State Physics Y1 - 1978 SN - 0022-3719 U6 - http://dx.doi.org/10.1088/0022-3719/11/15/031 VL - 11 IS - 15 SP - 3333 EP - 3344 PB - n.a. CY - London ER - TY - JOUR A1 - Ferrein, Alexander A1 - Steinbauer, Gerald T1 - Looking back on 20 Years of RoboCup JF - KI - Künstliche Intelligenz Y1 - 2016 U6 - http://dx.doi.org/10.1007/s13218-016-0443-y SN - 1610-1987 VL - 30 IS - 3-4 SP - 321 EP - 323 PB - Springer CY - Berlin ER -