Marcin Bator


Marcin Bator

Wydział Zastosowań Informatyki i Matematyki

Katedra Informatyki

+48 22 59 372 74


  1. M. Bator, L. J. Chmielewski, A. Orlowski, Heuristic Assessment of Parameters of the Local Ground Approximation from Terrestrial LIDAR Data, Image and Video Technology - PSIVT 2015 WORKSHOPS, eds. F. Huang, A. Sugimoto, LNCS 9555:88-97, 2016, 7th Pacific-R

  2. M. Bator, L. J. Chmielewski, A. Orlowski, Where Is the Ground? Quality Measures for the Planar Digital Terrain Model in Terrestrial Laser Scanning, Image Analysis and Processing - ICIAP 2015, PT I V. Murino, E. Puppo, LNCS 9279:343-353 2015, 18th Interna

  3. L. J. Chmielewski, M. Bator, M. Olejniczak, Advantages of Using Object-Specific Knowledge at an Early Processing Stage in the Detection of Trees in LIDAR Data, Computer Vision and Graphics, ICCVG 2014, eds. Chmielewski, et al., LNCS:145-154, 2014, Interna

  4. M. Zawidzki, M. Bator, Application of evolutionary algorithm for optimization of the sequence of initial conditions for the cellular automaton-based shading. Journal of Cellular Automata, 7(5/6):363-384, 2012.

  5. L.J. Chmielewski, M. Bator, Hough transform for opaque circles measured from outside and fuzzy voting for and against. Computer Vision and Graphics, eds. L. Bolc et al., Lecture Notes in Computer Science, 7594:313-320, 2012.

  6. T. Ząbkowski, M. Bator, A. Orłowski, Smart Metering – a Brief Overview of Projects, Benefits and Applications. Information Systems in Management, 1(1):72-83, 2012.

  7. M. Bator, M. Nieniewski, Detection of cancerous masses in mammograms by template matching: optimization of template brightness distribution by means of evolutionary algorithm. Journal of Digital Imaging, 25(1):162-172, 2012.

  8. L.J. Chmielewski, M. Bator, et al., Fuzzy Hough transform-based methods for extraction and measurements of single trees in large-volume 3D terrestrial LIDAR data. Computer Vision and Graphics, eds. L. Bolc et al., LNCS 6374:265-274, 2010.

  9. M. Bator, L. J. Chmielewski, Finding Regions of Interest for Cancerous Masses Enhanced by Elimination of Linear Structures and Considerations on Detection Correctness Measures in Mammography. Pattern Analysis & Applications, 12(4):377-390, 2009.

  10. M. Bator, M. Nieniewski, Template Matching by Means of Correlation Coefficient For Detecting Cancerous Masses. Machine Graphic and Vision, 16(3/4):329-345, 2007.

  11. M. Bator, L.J. Chmielewski, Elimination of Linear Structures as an Attempt to Improve the Specificity of Cancerous Mass Detection in Mammograms. Computer Recognition Systems 2, edt. M. Kurzynski et al., Advances in Soft Computing, 45:596-603, 2007.

  12. M. Bator, M. Ustymowicz, M. Nieniewski, Doświadczenia z detekcja mikrozwapnień oraz mas nowotworowych w mammogramach. Rozdział 18 w: Inteligentne wydobywanie informacji w celach diagnostycznych, red. Z. Kowalczuk, B. Wiszniewski,305-322, PWNT, Gdańsk 2007

  13. M. Bator, M. Nieniewski, The Usage of Template Matching and Multi-Resolution for Detecting Cancerous Masses in Mammograms. Medical Informatics & Technology, edt. E. Piętka et al., 324-329, 2006.