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Results: 295
Number of items: 295
  • Vlassis, N., Likas, A., & Kröse, B. J. A. (2000). A multivariate kurtosis-based approach to Gaussian misture modeling. (IAS-UVA; No. 00-04). Informatics Institute.
  • 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., Dev, A., & Groen, F. C. A. (2000). Heading Direction for a mobile robot from optic flow. Image and Vision Computing, 18(5), 415-424. https://doi.org/10.1016/S0262-8856(99)00036-0
  • Verbeek, J. J., Vlassis, N., & Kröse, B. J. A. (2000). A k-segments algorithm to finding principal curves. (IAS Uva; No. 00-11). Informatics Institute.
  • 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)
  • 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)
  • Vlassis, N., & Kröse, B. J. A. (1999). Mixture conditional density estimation with the EM algorithm. In ICANN'99, 9th Int. Conf. on Artificial Neural Networks (pp. 821-825). IEEE.
  • Vlassis, N., & Kröse, B. J. A. (1999). Robot environment modeling via principal component regression. In Proc. IROS'99, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (pp. 677-682)
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