Biblio

Found 231 results
[ Author(Desc)] Title Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
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Steil JJ.  1999.  Input-Output Stability of Recurrent Neural Networks.
Steil JJ, Kõiva R, Sperduti A.  2006.  Unsupervised Clustering of Continuous Trajectories of Kinematic Trees with SOM-SD. Proc. European Symposium on Artificial Neural Networks.
Steil JJ, Krüger S.  2013.  Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. Robotik und Gesetzgebung. 2:51–71.
Steil JJ, Heidemann G, Jockusch J, Rae R, Jungclaus N, Ritter H.  2001.  Guiding Attention for Grasping Tasks by Gestural Instruction: The GRAVIS-Robot Architecture. Proc. Int. Conf. Intelligent Robots and Sytems. :1570–1577.
Steil JJ, Cawley GC, Villmann T.  2005.  Trends in Neurocomputing at ESANN 2004. Neurocomputing. 64:1–4.
Steil JJ, Maier GW.  2018.  Kollaborative Roboter – universale Werkzeuge in der digitalisierten und vernetzten Arbeitswelt. Handbuch Gestaltung digitaler und vernetzter Arbeitswelten.
Steil JJ.  2002.  Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48:39–51.
Steil JJ, Sagerer G, Ritter H, Körner E.  2008.  Humans and Humanoids - Perspectives on Research in Cognition and Robotics. KI - Künstliche Intelligenz. 4:33–36.
Steil JJ, Ritter H.  1999.  Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. Proc. European Symposium Artificial Neural Networks. :369–374.
Steil JJ.  In Press.  Roboterlernen ohne Grenzen ? Lernende Roboter und ethische Fragen Christiane Woopen, Marc Jannes [Hrsg.] Roboter in der Gesellschaft. Technische Möglichkeiten und menschliche Verantwortung.
Steil JJ.  2005.  Stability of backpropagtion-decorrelation efficient O(N) recurrent learning. Proc. European Symposium Artificial Neural Networks. :43–48.
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Weirich A, Haumann C, Steil JJ, Schüler S..  2011.  Learning Lab - Physical Interaction with Humanoid Robots for Pupils. Proc. Robotics in Education. :21–28.
Weirich A, Schueler S, Haumann C, Steil JJ.  2010.  teutolab-robotik - Hands-On Teaching of Human-Robot Interaction. Proc. Int. Conf. on SIMULATION, MODELING and PROGRAMMING for AUTONOMOUS ROBOTS, Workshop on "Teaching Robotics-Teaching with Robotics". :474–483.
Weng S., Steil JJ.  2003.  Learning Compatibitlity Functions for Feature Binding and Perceptual Grouping. Proc. of Int. Conference Artificial Neural Networks. LNCS 2714:60–67.
Weng S, Wersing H, Steil JJ, Ritter H.  2006.  Learning Lateral Interactions for Feature Binding and Sensory Segmentation from Prototypic Basis Interactions. IEEE Trans. Neural Networks. 17:843–862.
Weng S., Steil JJ.  2002.  Data Driven Generation of Interactions for Feature Bindingand Relaxation Labeling. Proc. Int. Conf. Artificial Neural Networks. :432–437.
Wersing H, Steil JJ, Ritter H.  2001.  A Competitive Layer Model for Feature Binding and Sensory Segmentation. Neural Computation. 13:357–387.
Wersing H, Kirstein S, Götting M, Brandl H, Dunn M, Mikhailova I, Görick C, Steil JJ, Ritter H, Körner E.  2007.  Online Learning of Objects in a Biologically Motivated Visual Architecture. International Journal of Neural Systems. 17:219–230.
Wersing H, Steil JJ, Ritter H.  1997.  A Layered Recurrent Neural Network for Feature Grouping. Int. Conf. on Artificial Neural Networks. :439–444.
Wersing H, Götting M, Steil JJ.  2009.  Adaptive scene dependent filters in online learning environments.
Wersing H, Kirstein S, Götting M, Brandl H, Dunn M, Mikhailova I, Görick C, Steil JJ, Ritter H, Körner E.  2006.  A biologically motivated system for unconstrained online learning of visual objects. Proc. of the Int. Conf. on Artificial Neural Networks (ICANN). 2:508–517.
Wersing H, Kirstein S, Götting M, Brandl H, Dunn M, Mikhailova I, Görick C, Steil JJ, Ritter H, Körner E.  2007.  Online Learning of Objects and Faces in an Integrated Biologically Motivated Architecture. International Conference on Computer Vision Systems.
Wigand D, Mohammadi P, Hoffmann EMingo, Wrede S, Steil JJ, Tsagarakis N.  2018.  An Open-Source Architecture for Simulation, Execution and Analysis of Real-Time Robotics Systems. SIMPAR.

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