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Volumn , Issue , 2007, Pages 103-108

Visualization of fuzzy information in fuzzy-classification for image segmentationusing MDS

Author keywords

[No Author keywords available]

Indexed keywords

CLASS LABELS; CLASSIFICATION RESULTS; COLOR REPRESENTATION; COLOR SPACE; FUZZY CLASSIFICATION; FUZZY INFORMATION; LABEL INFORMATION; SIMILARITY PRESERVING;

EID: 42049097312     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (7)

References (12)
  • 2
    • 0028769579 scopus 로고
    • Fuzzy self-organizing map
    • Sept
    • Petri Vuorimaa. Fuzzy self-organizing map. Fuzzy Sets and Systems, 66(2):223-231, Sept 1994.
    • (1994) Fuzzy Sets and Systems , vol.66 , Issue.2 , pp. 223-231
    • Vuorimaa, P.1
  • 5
    • 33845571066 scopus 로고    scopus 로고
    • Analysis and visualization of proteomic data by fuzzy labeled self-organizing maps
    • In D.J. Lee, B. Nutter, S. Antani, S. Mitra, and J. Archibald, editors, IEEE Computer Society Press, Los Alamitos
    • F.-M. Schleif, T. Elssner, M. Kostrzewa, T. Villmann, and B. Hammer. Analysis and visualization of proteomic data by fuzzy labeled self-organizing maps. In D.J. Lee, B. Nutter, S. Antani, S. Mitra, and J. Archibald, editors, 19th IEEE International Symposium on Computer-based Medical Systems Salt Lake City (CBMS), pages 919-924. IEEE Computer Society Press, Los Alamitos, 2006.
    • (2006) 19th IEEE International Symposium On Computer-based Medical Systems Salt Lake City (CBMS) , pp. 919-924
    • Schleif, F.-M.1    Elssner, T.2    Kostrzewa, M.3    Villmann, T.4    Hammer, B.5
  • 6
    • 0002059002 scopus 로고    scopus 로고
    • Energy functions for self-organizing maps
    • In E. Oja and S. Kaski, editors, Elsevier, Amsterdam
    • T. Heskes. Energy functions for self-organizing maps. In E. Oja and S. Kaski, editors, Kohonen Maps, pages 303-316. Elsevier, Amsterdam, 1999.
    • (1999) Kohonen Maps , pp. 303-316
    • Heskes, T.1
  • 7
    • 0036791938 scopus 로고    scopus 로고
    • Generalized relevance learning vector quantization
    • B. Hammer and Th. Villmann. Generalized relevance learning vector quantization. Neural Networks, 15(8-9):1059-1068, 2002.
    • (2002) Neural Networks , vol.15 , Issue.8-9 , pp. 1059-1068
    • Hammer, B.1    Villmann, T.2
  • 11
    • 33646201094 scopus 로고    scopus 로고
    • High-Throughput Multi- Dimensional Scaling (HiT-MDS) for cDNA-array expression data
    • Part I, LNCS 3696, Pages W. Duch et al., editor, Springer
    • M. Strickert, S. Teichmann, N. Sreenivasulu, and U. Seiffert. High-Throughput Multi- Dimensional Scaling (HiT-MDS) for cDNA-array expression data. In W. Duch et al., editor, Artificial Neural Networks: Biological Inspirations, Part I, LNCS 3696, pages 625-634. Springer, 2005. http://hitmds.webhop.net/.
    • (2005) Artificial Neural Networks: Biological Inspirations , pp. 625-634
    • Strickert, M.1    Teichmann, S.2    Sreenivasulu, N.3    Seiffert, U.4
  • 12
    • 0026898892 scopus 로고
    • Quantifying the neighborhood preservation of Self- Organizing Feature Maps
    • H.-U. Bauer and K. R. Pawelzik. Quantifying the neighborhood preservation of Self- Organizing Feature Maps. IEEE Trans. on Neural Networks, 3(4):570-579, 1992.
    • (1992) IEEE Trans. On Neural Networks , vol.3 , Issue.4 , pp. 570-579
    • Bauer, H.-U.1    Pawelzik, K.R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.