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Results: 295
Number of items: 295
  • Kröse, B. J. A. (2000). An efficient representation of the robot's environment. In E. Pagello, F. Groen, T. Arai, R. Dillmann, & A. Stentz (Eds.), Proceedings Intelligent Autonomous Systems 6 (pp. 589-596). IOS Press.
  • Kröse, B. J. A., van den Bogaard, R., & Hietbrink, N. (2000). Programming robots is fun: Robocup Jr. 2000. In V. D. Bosch, & O. Weigand (Eds.), Proceedings of the Twelfth Belgium-Netherlands Al Conference BNAIC' 00 (pp. 29-36)
  • Portegies Zwart, J., & Kröse, B. J. A. (2000). Constraint mixture modeling of intrinsically low-dimensional distributions. In A. Sanfeliu, J. J. Villanueva, M. Vanrell, R. Alqu' ezar, A. K. Jain, & J. Kittler (Eds.), 15th International Conference on Pattern Recognition, Volume 2: Pattern Recognition and Neural Networks (Vol. 2, pp. 610-613). IEEE.
  • Vlassis, N., Motomura, Y., & Kröse, B. J. A. (2000). Supervised Linear Feature Extraction for Mobile Robot Localization. In Proceedings IEEE Int. Conf. on Robotics and Automation (pp. 2979-2984). IEEE.
  • Kröse, B. J. A., & Bunschoten, R. (1999). Probabilistic localization by appearance models and active vision. In Proc 1999 IEEE Int. Conf. on Robotics and Automation (pp. 2255-2260)
  • Kröse, B. J. A., Bunschoten, R., Vlassis, N., & Motomura, Y. (1999). Appearance based robot localization. In G. Kraetzschmar (Ed.), Proc. IJCAI-99 Workshop on adaptive spatial representations of dynamic environments (pp. 53-58)
  • ten Hagen, S. H. G., l' Ecluse, D., & Kröse, B. J. A. (1999). Q-Learning for Mobile Robot Control. In M. Gyssens, & E. Postma (Eds.), BNAIC'99, Proc. of the 11th Belgium-Netherlands Conference on Artificial Intelligence (pp. 203-210)
  • Vlassis, N., Motomura, Y., & Kröse, B. J. A. (1999). An information-theoretic localization criterion for robot map building. In Proc. ACAI'99, Int. Conf. on Machine Learning and Applications (pp. 1-6)
  • Motomura, Y., Vlassis, N., & Kröse, B. J. A. (1999). Probabilistic robot localization and situated feature focusing. In IEEE System, Machine and Cybernetics Conf, Tokyo
  • Motomura, Y., Vlassis, N., & Kröse, B. J. A. (1999). Environment modeling via PCA regression and situated feature focusing. In Proc. 24th SIG-MPS (Special Interest Group on Mathematical Modeling and Problem Solving) of the Information Processing Society of Japan, IPSJ SIG Notes vol.99 no.36 (Vol. 99, pp. 37-40)
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