Open Access
Issue
MATEC Web Conf.
Volume 255, 2019
Engineering Application of Artificial Intelligence Conference 2018 (EAAIC 2018)
Article Number 01001
Number of page(s) 5
Section Image Processing
DOI https://doi.org/10.1051/matecconf/201925501001
Published online 16 January 2019
  1. Y. Cheng, “Mean shift, mode seeking, and clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, pp. 790–799, 1995. [CrossRef] [Google Scholar]
  2. Yong-mei Zhou, Sheng-yi Jiang, and Mei-lin Yin, “A Region-based Image Segmentation Method with Mean-Shift Clustering Algorithm,” in Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008. FSKD ‘08 Jinan, China, 2008. [Google Scholar]
  3. Oncel Tuzel, Fatih Porikli, and Peter Meer, “Kernel Methods for Weakly Supervised Mean Shift Clustering,” in IEEE 12th International Conference on Computer Vision, ICCV 2009 Kyoto, Japan, 2009. [Google Scholar]
  4. R. O. Duda., P. E. Hart, and G. Stork, Pattern Classification. New York: John Wiley & Sons, 2000. [Google Scholar]
  5. J. C. Dunn, “A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well- Separated Clusters,” Journal of Cybernetics, vol. 3, pp. 32–57, 1973. [Google Scholar]
  6. Ping Wang and H. Wang;, “A Modified FCM Algorithm for MRI Brain Image Segmentation,” in International Seminar on Future BioMedical Information Engineering, 2008. FBIE ‘08 Wuhan, China, 2008. [Google Scholar]
  7. J.B MacQueen, “Some Methods for Classification and Analysis of Multivariate Observations,” in Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, California, 1967, pp. 281–297. [Google Scholar]
  8. G. H. Geng, M. Q. Zhou, “Characters Analysis of Current Algorithms for Quantization.” Mini-micro Systems, 1998, 19(9):46–49. [Google Scholar]

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