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Volumn 1, Issue , 2007, Pages 529-535

Curve clustering with spatial constraints for analysis of spatiotemporal data

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CHLORINE COMPOUNDS; CONFORMAL MAPPING; CYBERNETICS; FLOW OF SOLIDS; FOOD PROCESSING; IMAGE SEGMENTATION; LEARNING ALGORITHMS;

EID: 48649083737     PISSN: 10823409     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICTAI.2007.24     Document Type: Conference Paper
Times cited : (8)

References (15)
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    • 28344449679 scopus 로고
    • Bayesian image restoration with two applications in spatial statistics (with discussion)
    • J. Besag, J. York, and A. Mollie. Bayesian image restoration with two applications in spatial statistics (with discussion). Annals of the Institute of Statistical Mathematics, 43:1-59, 1991.
    • (1991) Annals of the Institute of Statistical Mathematics , vol.43 , pp. 1-59
    • Besag, J.1    York, J.2    Mollie, A.3
  • 5
    • 0142126680 scopus 로고    scopus 로고
    • Segmentation of dynamic PET or fMRI images based on a similarity metric
    • J. Brankov, N. Galatsanos, Y. Yang, and M. Wernick. Segmentation of dynamic PET or fMRI images based on a similarity metric. IEEE Trans. on Nuclear Science, 50(5):1410-1414, 2003.
    • (2003) IEEE Trans. on Nuclear Science , vol.50 , Issue.5 , pp. 1410-1414
    • Brankov, J.1    Galatsanos, N.2    Yang, Y.3    Wernick, M.4
  • 7
    • 0002629270 scopus 로고
    • Maximum Likelihood from incomplete data via the EM algorithm
    • A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum Likelihood from incomplete data via the EM algorithm. J. Roy. Statist. Soc. B, 39:1-38, 1977.
    • (1977) J. Roy. Statist. Soc. B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 8
    • 0001237218 scopus 로고
    • A maximum likelihood methodology for clusterwise linear regression
    • W. S. DeSarbo and W. L. Cron. A maximum likelihood methodology for clusterwise linear regression. Journal of Classification, 5(1):249-282, 1988.
    • (1988) Journal of Classification , vol.5 , Issue.1 , pp. 249-282
    • DeSarbo, W.S.1    Cron, W.L.2
  • 11
    • 0025404969 scopus 로고
    • Bayesian Reconstructions from Emission Tomography Data Using a Modified EM Algorithm
    • P. J. Green. Bayesian Reconstructions from Emission Tomography Data Using a Modified EM Algorithm. IEEE Trans. on Medical Imaging, 9(1):84-93, 1990.
    • (1990) IEEE Trans. on Medical Imaging , vol.9 , Issue.1 , pp. 84-93
    • Green, P.J.1
  • 12
    • 33750452323 scopus 로고    scopus 로고
    • Fast magnetization-driven preparation for imaging of contrast-enhanced coronary arteries during intra-arterial injection of contrast agent
    • D. Gui and N. V. Tsekos. Fast magnetization-driven preparation for imaging of contrast-enhanced coronary arteries during intra-arterial injection of contrast agent. J. Magn. Reson. Imaging, 24:1151-1158, 2006.
    • (2006) J. Magn. Reson. Imaging , vol.24 , pp. 1151-1158
    • Gui, D.1    Tsekos, N.V.2
  • 14
    • 34047208285 scopus 로고    scopus 로고
    • A class-adaptive spatially variant finite mixture model for image segmentation
    • C. Nikou, N. Galatsanos, and A. Likas. A class-adaptive spatially variant finite mixture model for image segmentation . IEEE Trans. on Image Processing, 14(4):1121-1130, 2007.
    • (2007) IEEE Trans. on Image Processing , vol.14 , Issue.4 , pp. 1121-1130
    • Nikou, C.1    Galatsanos, N.2    Likas, A.3
  • 15
    • 0034745001 scopus 로고    scopus 로고
    • Segmentation of Brain MR Images Through a Hidden Markov Random Field Model and the Expectation-Maximization Algorithm
    • Y. Zhang, M. Brady, and S. Smith. Segmentation of Brain MR Images Through a Hidden Markov Random Field Model and the Expectation-Maximization Algorithm. IEEE Trans. on Medical Imaging, 20(1):45-57, 2001.
    • (2001) IEEE Trans. on Medical Imaging , vol.20 , Issue.1 , pp. 45-57
    • Zhang, Y.1    Brady, M.2    Smith, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.