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Volumn 38, Issue 6, 1990, Pages 1039-1049

Stochastic and Deterministic Networks for Texture Segmentation

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL TECHNIQUES--ALGORITHMS; OPTIMIZATION; PROBABILITY--RANDOM PROCESSES;

EID: 0025449218     PISSN: 00963518     EISSN: None     Source Type: Journal    
DOI: 10.1109/29.56064     Document Type: Article
Times cited : (81)

References (23)
  • 1
    • 0023123263 scopus 로고
    • Modeling and segmentation of noisy and textured images using Gibbs random fields
    • Jan.
    • H. Derin and H. Elliott, “Modeling and segmentation of noisy and textured images using Gibbs random fields,” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-9, pp. 39–55, Jan. 1987.
    • (1987) IEEE Trans. Pattern Anal. Machine Intell. , vol.PAMI-9 , pp. 39-55
    • Derin, H.1    Elliott, H.2
  • 2
    • 0023312371 scopus 로고
    • Simple parallel hierarchical and relaxation algorithms for segmenting noncausal Markovian fields
    • Mar.
    • F. S. Cohen and D. B. Cooper, “Simple parallel hierarchical and relaxation algorithms for segmenting noncausal Markovian fields.” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-9, pp. 195–219, Mar. 1987.
    • (1987) IEEE Trans. Pattern Anal. Machine Intell. , vol.PAMI-9 , pp. 195-219
    • Cohen, F.S.1    Cooper, D.B.2
  • 3
    • 0021518209 scopus 로고
    • Stochastic relaxation, Gibbs distributions, and Bayesian restoration of images
    • Nov.
    • S. Geman and D. Geman, “Stochastic relaxation, Gibbs distributions, and Bayesian restoration of images,” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, pp. 721–741, Nov. 1984.
    • (1984) IEEE Trans. Pattern Anal. Machine Intell. , vol.PAMI-6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 4
    • 0022417790 scopus 로고
    • Computational vision and regularization theory
    • Sept.
    • T. Poggio, V. Torre, and C. Koch, “Computational vision and regularization theory,” Nature, vol. 317, pp. 314-319, Sept. 1985.
    • (1985) Nature , vol.317 , pp. 314-319
    • Poggio, T.1    Torre, V.2    Koch, C.3
  • 8
    • 0024122606 scopus 로고    scopus 로고
    • Computation of optical flow using a neural network
    • (San Diego, CA)
    • Y. T. Zhou and R. Chellappa, “Computation of optical flow using a neural network,” in Proc. IEEE Int. Conf. Neural Networks, vol. 2 (San Diego, CA), pp. 71–78.
    • Proc. IEEE Int. Conf. Neural Networks , vol.2 , pp. 71-78
    • Zhou, Y.T.1    Chellappa, R.2
  • 9
    • 0024551777 scopus 로고
    • A parallel algorithm for realtime computation of optical flow
    • Feb.
    • H. Bulthoff, J. Little, and T. Poggio, “A parallel algorithm for realtime computation of optical flow,” Nature, vol. 337, pp. 549–553. Feb. 1989.
    • (1989) Nature , vol.337 , pp. 549-553
    • Bulthoff, H.1    Little, J.2    Poggio, T.3
  • 10
    • 0021835689 scopus 로고
    • Neural computation of decisions in optimization problems
    • J. J. Hopfield and D. W. Tank, “Neural computation of decisions in optimization problems,” Biolog. Cybernet., vol. 52, pp. 114–152, 1985.
    • (1985) Biolog. Cybernet. , vol.52 , pp. 114-152
    • Hopfield, J.J.1    Tank, D.W.2
  • 11
    • 0000013152 scopus 로고
    • On the statistical analysis of dirty pictures
    • J. Besag, “On the statistical analysis of dirty pictures,” J. Roy. Statist. Soc. B. vol. 48, pp. 259–302, 1986.
    • (1986) J. Roy. Statist. Soc. B. , vol.48 , pp. 259-302
    • Besag, J.1
  • 15
    • 0002480122 scopus 로고
    • Two-dimensional discrete Gaussian Markov random field models for image processing
    • L. N. Kanal and A. Rosenfeld, Eds. New York: Elsevier
    • R. Chellappa, “Two-dimensional discrete Gaussian Markov random field models for image processing.” in Progress in Pattern Recognition 2, L. N. Kanal and A. Rosenfeld, Eds. New York: Elsevier, 1985, pp. 79–112.
    • (1985) Progress in Pattern Recognition , vol.2 , pp. 79-112
    • Chellappa, R.1
  • 17
    • 0022102621 scopus 로고
    • Classification of textures using Gaussian-Markov random fields
    • Aug.
    • R. Chellappa and S. Chatterjee, “Classification of textures using Gaussian-Markov random fields,” IEEE Trans. Acoust., Speech. Signal Process., vol. ASSP-33, pp. 959–963, Aug. 1985.
    • (1985) IEEE Trans. Acoust., Speech. Signal Process. , vol.ASSP-33 , pp. 959-963
    • Chellappa, R.1    Chatterjee, S.2
  • 18
    • 0002199090 scopus 로고
    • Markov random fields image models and their application to computer vision
    • (Providence).
    • S. Geman and C. Gratligne, “Markov random fields image models and their application to computer vision,” in Proc. Int. Congress of Mathematicans 1986 (Providence).
    • (1986) Proc. Int. Congress of Mathematicans
    • Geman, S.1    Gratligne, C.2
  • 19
    • 0012667451 scopus 로고
    • Probabilistic solution of ill-posed problems in computer vision
    • (Miami Beach. FL). Dec.
    • J. Marroquin, S. Mitter, and T. Poggio, “Probabilistic solution of ill-posed problems in computer vision,” in Proc. Image Understanding Workshop (Miami Beach. FL). Dec. 1985, pp. 293–309.
    • (1985) Proc. Image Understanding Workshop , pp. 293-309
    • Marroquin, J.1    Mitter, S.2    Poggio, T.3
  • 20
    • 0001939254 scopus 로고
    • Non-stationary Markov chains and convergence of the annealing algorithm
    • B. Gidas, “Non-stationary Markov chains and convergence of the annealing algorithm.” J. Statist. Phys., vol. 39, pp. 73–131, 1985.
    • (1985) J. Statist. Phys. , vol.39 , pp. 73-131
    • Gidas, B.1
  • 21
    • 0022738693 scopus 로고
    • Decentralized learning in finite Markov chains
    • June
    • R. M. Wheeler. Jr., and K. S. Narendra, “Decentralized learning in finite Markov chains.” IEEE Trans. Automat. Contr., vol. AC-31, pp. 519–526, June 1986.
    • (1986) IEEE Trans. Automat. Contr. , vol.AC-31 , pp. 519-526
    • Wheeler, R.M.1    Narendra, K.S.2
  • 23
    • 0022184180 scopus 로고
    • Maximum likelihood texture segmentation using Gaussian Markov random field models
    • (San Francisco. CA). June
    • S. Chatterjee and R. Chellappa, “Maximum likelihood texture segmentation using Gaussian Markov random field models.” in Proc. Computer Vision and Pattern Recognition Conf. (San Francisco. CA). June 1985.
    • (1985) Proc. Computer Vision and Pattern Recognition Conf.
    • Chatterjee, S.1    Chellappa, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.