Biblio

Found 784 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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Last P., Hesselbach J., Wahl F..  2005.  Hochdynamische Parallelroboter im Bereich Handhabung und Montage. GMA-Kongress 2005. :243–253.
Last C., Winkelbach S., Wahl F., Eichhorn K., Bootz F..  2011.  A Locally Deformable Statistical Shape Model. MLMI 2011, LNCS. 7009:51–58.
Last C., Winkelbach S., Wahl F., Eichhorn K., Bootz F..  2010.  A Model-Based Approach to the Segmentation of Nasal Cavity and Paranasal Sinus Boundaries. Pattern Recognition (Proc. of DAGM 2010),. 6376:333–342.
[Anonymous].  2005.  Proceedings of the Second International Colloquium 'Collaborative Research Centre 562. Fortschritte in der Robotik.
Last C., Winkelbach S., Wahl F..  2013.  VMV 2013: Vision, Modeling & Visualization. :153–160.
Last C., Winkelbach S..  2014.  Global-to-Local Statistical Shape Priors. Shape 2014 - Symposium on Statistical Shape Models and Applications.
Last C., Sommerkorn A., Westphal R., Wiebking U., Krettek C., Wahl F..  2012.  Fully automatic knee CT image segmentation with locally adaptive shape priors (Poster). CARS 2012.
Lebedev DV, Steil JJ, Ritter H.  2005.  An on-line neural network-based approach to dynamic path planning and coordination of two robot arms. Proc. Int. Conf. Intelligent Robotis and Systems. :2411–2416.
Lebedev DV, Steil JJ, Ritter H.  2003.  Real Time Path Planning in Dynamic Environment: a Comparison of Three Neural Network Models. Proc. IEEE Int. Conf. Systems, Man, and Cybernetics. :3408–3413.
Lebedev DV, Steil JJ, Ritter H.  2002.  A New Wave Neural Network Dynamics for Planning Safe Paths of Autonomous Objects in a Dynamically Changing World. Advances in Neural Networks World. :141–146.
Lebedev DV, Steil JJ, Ritter H.  2003.  A Neural Network Model that Calculates Dynamic Distance Transform for Path Planning and Exploration in a Changing Environment. Proc. IEEE Int. Conf. on Robotics and Automation. :4209–4214.
Lemme A, Reinhart F, Steil JJ.  2010.  Efficient online learning of a non-negative sparse autoencoder. European Symposium Artificial Neural Networks. :1–6.
Lemme A, Reinhart F, Neumann K, Steil JJ.  2014.  Neural Learning of Vector Fields for Encoding Stable Dynamical Systems. Neurocomputing. 141:3–14.
Lemme A, Meirovitch Y, Khansari-Zadeh SMohammad, Flash T, Billard A, Steil JJ.  2015.  Open-source benchmarking for learned reaching motion generation in robotics. Paladyn, Journal of Behavioral Robotics. 6:30–41.
Lemme A, Reinhart F, Steil JJ.  2012.  Online learning and generalization of parts-based image representations by Non-Negative Sparse Autoencoders. Neural Networks. 33:194–203.
Lemme A, Neumann K, Reinhart F, Steil JJ.  2013.  Neurally imprinted stable vector fields. ESANN. :327–332.
Lemme A, Steil JJ.  2015.  A flat neural network architecture to represent movement primitives with integrated sequencing. :481–486.
Lemme A, Freire A, Barreto G, Steil JJ.  2013.  Kinesthetic teaching of visuomotor coordination for pointing by the humanoid robot iCub. Neurocomputing. 112:179–188.
Lemme A, Reinhart F, Steil JJ.  2014.  Semi-supervised Bootstrapping of a Movement Primitive Library from Complex Trajectories. :726–732.
Li W., Chang X., Wahl F..  1999.  Mechatronics. 9:301–315.
Li W., Wahl F..  1998.  Vision Navigation of an Autonomous Vehicle by Fuzzy Reasoning. IX European Signal Processing Conference. IV:2113–2116.
Li W., Chang X., Wahl F., Farrell J..  2001.  Tracking control of a manipulator under uncertainty by FUZZY P+ID controller. Fuzzy Sets and Systems. 122:125–137.
Li W., Ma B., Wahl F..  1997.  A neuro-fuzzy system architecture for behavior-based control of a mobile robot in unkown environments. Fuzzy Sets and Systems. 87:133–140.
Li W., Chang X., Wahl F..  2001.  Design of an Enhanced Hybrid Fuzzy P+ID Controller for a Mechanical Manipulator. IEEE Transactions on Systems, Man and Cybernetics - Part B. 31:938–945.
Li W., Wahl F., Krebs B..  1999.  Extraction of line and step edges by fuzzy reasoning. International Conference on Computational Intelligence for Modelling, Control and Automation. :507–512.

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