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Volumn 31, Issue 12, 1998, Pages 2103-2118

The advanced distributed region of interest tool

Author keywords

Fractal dimension; Genetic algorithms; Low level vision; Mixture models; Statistical pattern recognition

Indexed keywords

FRACTALS; GENETIC ALGORITHMS; PROBABILITY DENSITY FUNCTION; STATISTICAL METHODS;

EID: 0032319134     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(98)00025-9     Document Type: Article
Times cited : (9)

References (22)
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    • Mallat, S.1    Zhong, S.2
  • 8
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    • Multiscale fractal theory and object characterization
    • 8. T. Peli, Multiscale fractal theory and object characterization J. Opt. Soc. Am. A7(6), 1101-1112 (1991).
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    • A PDP approach to localized fractal dimension computation with segmentation boundaries
    • 11. G. W. Rogers, C. E. Priebe and J. L. Solka, A PDP approach to localized fractal dimension computation with segmentation boundaries, Simulation 65(1), 26-36 (1995).
    • (1995) Simulation , vol.65 , Issue.1 , pp. 26-36
    • Rogers, G.W.1    Priebe, C.E.2    Solka, J.L.3
  • 12
    • 0043035374 scopus 로고
    • Calculation of power law features in the presence of segmentation utilizing a Dijkstra potential based algorithm
    • April 10-15, San Diego, California
    • 12. E. G. Julin, G. W. Rogers, C. E. Priebe and J. L. Solka, Calculation of power law features in the presence of segmentation utilizing a Dijkstra potential based algorithm, Proc. High Performance Computing; 1994 Simulation Multiconference, April 10-15, San Diego, California, pp. 357-362 (1994).
    • (1994) Proc. High Performance Computing; 1994 Simulation Multiconference , pp. 357-362
    • Julin, E.G.1    Rogers, G.W.2    Priebe, C.E.3    Solka, J.L.4
  • 13
    • 0039195867 scopus 로고
    • Calculation and comparison of fractal dimension distributions
    • San Diego, California, July 18-20
    • 13. G. W. Rogers, C. E. Priebe and E. G. Julin, Calculation and comparison of fractal dimension distributions, Proc. 1994 Summer Computer Simulation Conf., San Diego, California, July 18-20 pp. 223-229 (1994).
    • (1994) Proc. 1994 Summer Computer Simulation Conf. , pp. 223-229
    • Rogers, G.W.1    Priebe, C.E.2    Julin, E.G.3
  • 14
    • 34250761450 scopus 로고    scopus 로고
    • A genetic algorithm for best subset selection in linear regression
    • 14. B. C. Wallet, D. J. Marchette, J. L. Solka and E. J. Wegman, A genetic algorithm for best subset selection in linear regression, Interface 96 (1996). Vol 28, pp 545-550.
    • (1996) Interface 96 , vol.28 , pp. 545-550
    • Wallet, B.C.1    Marchette, D.J.2    Solka, J.L.3    Wegman, E.J.4
  • 16
    • 0025573202 scopus 로고
    • Pattern classification using projection pursuit
    • 16. T. E. Flick, L. K. Jones, R. G. Priest and C. Herman, Pattern classification using projection pursuit, Pattern Recognition 23(12) 1367-1376 (1990).
    • (1990) Pattern Recognition , vol.23 , Issue.12 , pp. 1367-1376
    • Flick, T.E.1    Jones, L.K.2    Priest, R.G.3    Herman, C.4
  • 18
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    • Adaptive mixtures: Recursive nonparametric pattern recognition
    • 18. C. E. Priebe and D. J. Marchette, Adaptive mixtures: recursive nonparametric pattern recognition, Pattern Recognition 24(12), 1197-1209 (1991).
    • (1991) Pattern Recognition , vol.24 , Issue.12 , pp. 1197-1209
    • Priebe, C.E.1    Marchette, D.J.2
  • 22
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    • Nonhomogeneity analysis using borrowed strength
    • 22. C. E. Priebe, Nonhomogeneity analysis using borrowed strength, J. Am. Statist. Assoc. 91, 1497-1503 (1996).
    • (1996) J. Am. Statist. Assoc. , vol.91 , pp. 1497-1503
    • Priebe, C.E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.