Publication Downloads

  1. Peters, J.F., Near sets. General theory about nearness of objects, Applied Mathematical Sciences 1 (53) (2007) 2609-2029. http://www.m-hikari.com/ams/forth/petersAMS53-56-2007.pdf
  2. Lockery, D., Peters, J.F., 2007, Robotic target tracking with approximation space-based feedback during reinforcement learning, Springer best paper award, in: Proceedings of Eleventh International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2007), Joint Rough Set Symposium (JRS 2007), Lecture Notes in Artificial Intelligence, vol. 4482, pp. 483-490.
  3. Borkowski, M., Peters, J.F.: Matching 2D image segments with genetic algorithms and approximation spaces. Transactions on Rough Sets V, LNCS 4100 (2006), 63-101.
  4. Henry, C., Peters, J.F., 2007, Image Pattern Recognition Using Approximation Spaces and Near Sets, In: Proceedings of Eleventh International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2007), Joint Rough Set Symposium (JRS 2007), Lecture Notes in Artificial Intelligence, vol. 4482, pp. 475-482.
  5. J.F. Peters, M. Borkowski, C. Henry, D. Lockery, Monocular vision system that learns with approximation spaces. In: Hassanien, A.E., Slezak, D., Suraj, Z., Lingras, P. (Eds.), Rough Set Computing: Toward Perception Based Computing, Idea Group Publishing, Hershey, PA (2006), 1-22.
  6. Skowron, A., Stepaniuk, J., Peters, J.F., Swiniarski, R.: Calculi of approximation spaces. Fundamenta Informaticae 72(2006) 363-378.
  7. J.F. Peters, S. Shahfar, S. Ramanna, T. Szturm, Biologically-inspired adaptive learning: A near set approach, In: Proc. Frontiers in the Convergence of Bioscience and Information Technologies (FBIT07), IEEE, NJ, 11 October 2007, in press.