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Volumn 24, Issue 10, 2015, Pages 3124-3136

Efficient Robust Conditional Random Fields

Author keywords

Conditional random fields; Image segmentation; Optimal gradient method; Robust conditional random fields

Indexed keywords

BIOINFORMATICS; COMPUTER VISION; GRADIENT METHODS; ITERATIVE METHODS; RANDOM PROCESSES;

EID: 84933052910     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2015.2438553     Document Type: Article
Times cited : (18)

References (59)
  • 1
    • 77955783919 scopus 로고    scopus 로고
    • Fast image recovery using variable splitting and constrained optimization
    • Sep.
    • M. V. Afonso, J. M. Bioucas-Dias, and M. A. T. Figueiredo, "Fast image recovery using variable splitting and constrained optimization", IEEE Trans. Image Process., vol. 19, no. 9, pp. 2345-2356, Sep. 2010.
    • (2010) IEEE Trans. Image Process. , vol.19 , Issue.9 , pp. 2345-2356
    • Afonso, M.V.1    Bioucas-Dias, J.M.2    Figueiredo, M.A.T.3
  • 2
    • 85014561619 scopus 로고    scopus 로고
    • A fast iterative shrinkage-thresholding algorithm for linear inverse problems
    • A. Beck and M. Teboulle, "A fast iterative shrinkage-thresholding algorithm for linear inverse problems", SIAM J. Image Sci., vol. 2, no. 1, pp. 183-202, 2009.
    • (2009) SIAM J. Image Sci. , vol.2 , Issue.1 , pp. 183-202
    • Beck, A.1    Teboulle, M.2
  • 3
    • 77953690109 scopus 로고    scopus 로고
    • Multiplicative noise removal using variable splitting and constrained optimization
    • Jul
    • J. M. Bioucas-Dias and M. A. T. Figueiredo, "Multiplicative noise removal using variable splitting and constrained optimization", IEEE Trans. Image Process., vol. 19, no. 7, pp. 1720-1730, Jul. 2010.
    • (2010) IEEE Trans. Image Process. , vol.19 , Issue.7 , pp. 1720-1730
    • Bioucas-Dias, J.M.1    Figueiredo, M.A.T.2
  • 4
    • 0002652285 scopus 로고    scopus 로고
    • A maximum entropy approach to natural language processing
    • Mar.
    • A. L. Berger, V. J. D. Pietra, and S. A. D. Pietra, "A maximum entropy approach to natural language processing", Comput. Linguistics, vol. 22, no. 1, pp. 39-71, Mar. 1996.
    • (1996) Comput. Linguistics , vol.22 , Issue.1 , pp. 39-71
    • Berger, A.L.1    Pietra, V.J.D.2    Pietra, S.A.D.3
  • 5
    • 80053974159 scopus 로고    scopus 로고
    • 3D segmentation in CT imagery with conditional random fields and histograms of oriented gradients
    • C. Bhole, N. Morsillo, and C. Pal, "3D segmentation in CT imagery with conditional random fields and histograms of oriented gradients", in Proc. 2nd Int. Conf. Mach. Learn. Med. Imag., 2011, pp. 326-334.
    • (2011) Proc. 2nd Int. Conf. Mach. Learn. Med. Imag. , pp. 326-334
    • Bhole, C.1    Morsillo, N.2    Pal, C.3
  • 7
    • 0000582521 scopus 로고
    • Statistical analysis of non-lattice data
    • Sep.
    • J. Besag, "Statistical analysis of non-lattice data", J. Roy. Statist. Soc. D, vol. 24, no. 3, pp. 179-195, Sep. 1975.
    • (1975) J. Roy. Statist. Soc. D , vol.24 , Issue.3 , pp. 179-195
    • Besag, J.1
  • 8
    • 0003713964 scopus 로고    scopus 로고
    • 2nd ed. Belmont, MA, USA: Athena Scientific
    • P. D. Bertsekas, Nonlinear Programming, 2nd ed. Belmont, MA, USA: Athena Scientific, 1999.
    • (1999) Nonlinear Programming
    • Bertsekas, P.D.1
  • 10
    • 85127836544 scopus 로고    scopus 로고
    • Discriminative training methods for hidden Markov models: Theory and experiments with perceptron algorithms
    • M. Collins, "Discriminative training methods for hidden Markov models: Theory and experiments with perceptron algorithms", in Proc. Empirical Methods Natural Lang. Process., vol. 10. 2002, pp. 1-8.
    • (2002) Proc. Empirical Methods Natural Lang. Process. , vol.10 , pp. 1-8
    • Collins, M.1
  • 11
    • 84893847895 scopus 로고    scopus 로고
    • Insights into analysis operator learning: From patch-based sparse models to higher order MRFs
    • Mar.
    • Y. Chen, R. Ranftl, and T. Pock, "Insights into analysis operator learning: From patch-based sparse models to higher order MRFs", IEEE Trans. Image Process., vol. 23, no. 3, pp. 1060-1072, Mar. 2014.
    • (2014) IEEE Trans. Image Process. , vol.23 , Issue.3 , pp. 1060-1072
    • Chen, Y.1    Ranftl, R.2    Pock, T.3
  • 12
    • 0018925643 scopus 로고
    • Two-dimensional spectral analysis of cortical receptive field profiles
    • J. G. Daugman, "Two-dimensional spectral analysis of cortical receptive field profiles", Vis. Res., vol. 20, no. 10, pp. 847-856, 1980.
    • (1980) Vis. Res. , vol.20 , Issue.10 , pp. 847-856
    • Daugman, J.G.1
  • 15
    • 78649287919 scopus 로고    scopus 로고
    • Restoration of Poissonian images using alternating direction optimization
    • Dec.
    • M. A. T. Figueiredo and J. M. Bioucas-Dias, "Restoration of Poissonian images using alternating direction optimization", IEEE Trans. Image Process., vol. 19, no. 12, pp. 3133-3145, Dec. 2010.
    • (2010) IEEE Trans. Image Process. , vol.19 , Issue.12 , pp. 3133-3145
    • Figueiredo, M.A.T.1    Bioucas-Dias, J.M.2
  • 16
    • 35148870866 scopus 로고    scopus 로고
    • Conformal embedding analysis with local graph modeling on the unit hypersphere
    • Jun.
    • Y. Fu, M. Liu, and T. S. Huang, "Conformal embedding analysis with local graph modeling on the unit hypersphere", in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2007, pp. 1-6.
    • (2007) Proc. IEEE Conf. Comput. Vis. Pattern Recognit. , pp. 1-6
    • Fu, Y.1    Liu, M.2    Huang, T.S.3
  • 17
    • 0013344078 scopus 로고    scopus 로고
    • Training products of experts by minimizing contrastive divergence
    • Aug.
    • G. E. Hinton, "Training products of experts by minimizing contrastive divergence", Neural Comput., vol. 14, no. 8, pp. 1771-1800, Aug. 2002.
    • (2002) Neural Comput. , vol.14 , Issue.8 , pp. 1771-1800
    • Hinton, G.E.1
  • 20
    • 84898983746 scopus 로고    scopus 로고
    • Discriminative fields for modeling spatial dependencies in natural images
    • S. Kumar and M. Hebert, "Discriminative fields for modeling spatial dependencies in natural images", in Proc. Adv. Neural Inf. Process. Syst., vol. 16. 2004.
    • (2004) Proc. Adv. Neural Inf. Process. Syst. , vol.16
    • Kumar, S.1    Hebert, M.2
  • 22
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • Nov.
    • D. G. Lowe, "Distinctive image features from scale-invariant keypoints", Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, Nov. 2004.
    • (2004) Int. J. Comput. Vis. , vol.60 , Issue.2 , pp. 91-110
    • Lowe, D.G.1
  • 24
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • J. D. Lafferty, A. McCallum, and F. C. N. Pereira, "Conditional random fields: Probabilistic models for segmenting and labeling sequence data", in Proc. 18th Int. Conf. Mach. Learn., 2001, pp. 282-289.
    • (2001) Proc. 18th Int. Conf. Mach. Learn. , pp. 282-289
    • Lafferty, J.D.1    McCallum, A.2    Pereira, F.C.N.3
  • 25
    • 84867839897 scopus 로고    scopus 로고
    • Modeling complex temporal composition of actionlets for activity prediction
    • K. Li, J. Hu, and Y. Fu, "Modeling complex temporal composition of actionlets for activity prediction", in Proc. Eur. Conf. Comput. Vis., 2012, pp. 286-299.
    • (2012) Proc. Eur. Conf. Comput. Vis. , pp. 286-299
    • Li, K.1    Hu, J.2    Fu, Y.3
  • 26
    • 84930628204 scopus 로고    scopus 로고
    • Multiview alignment hashing for efficient image search
    • Mar.
    • L. Liu, M. Yu, and L. Shao, "Multiview alignment hashing for efficient image search", IEEE Trans. Image Process., vol. 24, no. 3, pp. 956-966, Mar. 2015.
    • (2015) IEEE Trans. Image Process. , vol.24 , Issue.3 , pp. 956-966
    • Liu, L.1    Yu, M.2    Shao, L.3
  • 27
    • 0018457301 scopus 로고
    • A separator theorem for planar graphs
    • R. J. Lipton and R. E. Tarjan, "A separator theorem for planar graphs", SIAM J. Appl. Math., vol. 36, no. 2, pp. 177-189, 1979.
    • (1979) SIAM J. Appl. Math. , vol.36 , Issue.2 , pp. 177-189
    • Lipton, R.J.1    Tarjan, R.E.2
  • 28
    • 84896061548 scopus 로고    scopus 로고
    • Low-rank coding with b-matching constraint for semisupervised classification
    • S. Li and Y. Fu, "Low-rank coding with b-matching constraint for semisupervised classification", in Proc. 23rd Int. Joint Conf. Artif. Intell., 2013, pp. 1472-1478.
    • (2013) Proc. 23rd Int. Joint Conf. Artif. Intell. , pp. 1472-1478
    • Li, S.1    Fu, Y.2
  • 29
    • 1042264823 scopus 로고    scopus 로고
    • A comparison of algorithms for maximum entropy parameter estimation
    • R. Malouf, "A comparison of algorithms for maximum entropy parameter estimation", in Proc. COLING, 2002, pp. 1-7.
    • (2002) Proc. COLING , pp. 1-7
    • Malouf, R.1
  • 32
    • 34548480020 scopus 로고
    • A method for solving a convex programming problem with convergence rate O (1/k2)
    • Y. Nesterov, "A method for solving a convex programming problem with convergence rate O (1/k2)", Soviet Math. Doklady, vol. 27, no. 2, pp. 372-376, 1983.
    • (1983) Soviet Math. Doklady , vol.27 , Issue.2 , pp. 372-376
    • Nesterov, Y.1
  • 33
    • 17444406259 scopus 로고    scopus 로고
    • Smooth minimization of non-smooth functions
    • May
    • Y. Nesterov, "Smooth minimization of non-smooth functions", Math. Program., vol. 103, no. 1, pp. 127-152, May 2005.
    • (2005) Math. Program. , vol.103 , Issue.1 , pp. 127-152
    • Nesterov, Y.1
  • 36
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • Dec.
    • S. T. Roweis and L. K. Saul, "Nonlinear dimensionality reduction by locally linear embedding", Science, vol. 290, no. 5500, pp. 2323-2326, Dec. 2000.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 39
    • 72949123287 scopus 로고    scopus 로고
    • Biologically inspired feature manifold for scene classification
    • Jan.
    • D. Song and D. Tao, "Biologically inspired feature manifold for scene classification", IEEE Trans. Image Process., vol. 19, no. 1, pp. 174-184, Jan. 2010.
    • (2010) IEEE Trans. Image Process. , vol.19 , Issue.1 , pp. 174-184
    • Song, D.1    Tao, D.2
  • 40
    • 84933037003 scopus 로고    scopus 로고
    • Rank preserving hashing for rapid image search
    • Snowbird, UT, USA
    • D. Song, W. Liu, D. A. Meyer, R. Ji, and D. Tao, "Rank preserving hashing for rapid image search", in Proc. Data Compress. Conf., Snowbird, UT, USA, 2015, pp. 353-362.
    • (2015) Proc. Data Compress. Conf. , pp. 353-362
    • Song, D.1    Liu, W.2    Meyer, D.A.3    Ji, R.4    Tao, D.5
  • 42
    • 27544451563 scopus 로고    scopus 로고
    • RNA secondary structural alignment with conditional random fields
    • K. Sato and Y. Sakakibara, "RNA secondary structural alignment with conditional random fields", Bioinformatics, vol. 21, no. 2, pp. 237-242, 2005.
    • (2005) Bioinformatics , vol.21 , Issue.2 , pp. 237-242
    • Sato, K.1    Sakakibara, Y.2
  • 43
    • 84903154900 scopus 로고    scopus 로고
    • From heuristic optimization to dictionary learning: A review and comprehensive comparison of image denoising algorithms
    • Jul
    • L. Shao, R. Yan, X. Li, and Y. Liu, "From heuristic optimization to dictionary learning: A review and comprehensive comparison of image denoising algorithms", IEEE Trans. Cybern., vol. 44, no. 7, pp. 1001-1013, Jul. 2014.
    • (2014) IEEE Trans. Cybern. , vol.44 , Issue.7 , pp. 1001-1013
    • Shao, L.1    Yan, R.2    Li, X.3    Liu, Y.4
  • 44
    • 84910597067 scopus 로고    scopus 로고
    • Learning deep and wide: A spectral method for learning deep networks
    • Dec.
    • L. Shao, D. Wu, and X. Li, "Learning deep and wide: A spectral method for learning deep networks", IEEE Trans. Neural Netw. Learn. Syst., vol. 25, no. 12, pp. 2303-2308, Dec. 2014.
    • (2014) IEEE Trans. Neural Netw. Learn. Syst. , vol.25 , Issue.12 , pp. 2303-2308
    • Shao, L.1    Wu, D.2    Li, X.3
  • 45
    • 78649299942 scopus 로고    scopus 로고
    • Efficient learning of sparse conditional random fields for supervised sequence labeling
    • Dec.
    • N. Sokolovska, T. Lavergne, O. Cappé, and F. Yvon, "Efficient learning of sparse conditional random fields for supervised sequence labeling", IEEE J. Sel. Topics Signal Process., vol. 4, no. 6, pp. 953-964, Dec. 2010.
    • (2010) IEEE J. Sel. Topics Signal Process. , vol.4 , Issue.6 , pp. 953-964
    • Sokolovska, N.1    Lavergne, T.2    Cappé, O.3    Yvon, F.4
  • 47
    • 84926214098 scopus 로고    scopus 로고
    • Principal component 2-dimensional long short-term memory for font recognition on single Chinese characters
    • to be published
    • D. Tao, X. Lin, L. Jin, and X. Li, "Principal component 2-dimensional long short-term memory for font recognition on single Chinese characters", IEEE Trans. Cybern., to be published, doi: 10.1109/TCYB.2015.2414920.
    • IEEE Trans. Cybern.
    • Tao, D.1    Lin, X.2    Jin, L.3    Li, X.4
  • 48
    • 70349451222 scopus 로고    scopus 로고
    • CoCRF deformable model: A geometric model driven by collaborative conditional random fields
    • Oct.
    • G. Tsechpenakis and D. Metaxas, "CoCRF deformable model: A geometric model driven by collaborative conditional random fields", IEEE Trans. Image Process., vol. 18, no. 10, pp. 2316-2329, Oct. 2009.
    • (2009) IEEE Trans. Image Process. , vol.18 , Issue.10 , pp. 2316-2329
    • Tsechpenakis, G.1    Metaxas, D.2
  • 50
    • 84885382627 scopus 로고    scopus 로고
    • Markov random field modeling, inference & learning in computer vision & image understanding: A survey
    • Nov.
    • C. Wang, N. Komodakis, and N. Paragios, "Markov random field modeling, inference & learning in computer vision & image understanding: A survey", Comput. Vis. Image Understand., vol. 117, no. 11, pp. 1610-1627, Nov. 2013.
    • (2013) Comput. Vis. Image Understand. , vol.117 , Issue.11 , pp. 1610-1627
    • Wang, C.1    Komodakis, N.2    Paragios, N.3
  • 51
    • 33749241036 scopus 로고    scopus 로고
    • Comparing the mean field method and belief propagation for approximate inference in MRFs
    • D. Saad and M. Opper, Eds. Cambridge, MA, USA: MIT Press
    • Y. Weiss, "Comparing the mean field method and belief propagation for approximate inference in MRFs", in Advanced Mean Field Methods, D. Saad and M. Opper, Eds. Cambridge, MA, USA: MIT Press, 2001.
    • (2001) Advanced Mean Field Methods
    • Weiss, Y.1
  • 52
    • 84897479364 scopus 로고    scopus 로고
    • Sparse Gaussian conditional random fields: Algorithms, theory, and application to energy forecasting
    • M. Wytock and Z. Kolter, "Sparse Gaussian conditional random fields: Algorithms, theory, and application to energy forecasting", in Proc. 30th Int. Conf. Mach. Learn., 2013, pp. 1265-1273.
    • (2013) Proc. 30th Int. Conf. Mach. Learn. , pp. 1265-1273
    • Wytock, M.1    Kolter, Z.2
  • 53
    • 84904192140 scopus 로고    scopus 로고
    • Large-margin multi-view information bottleneck
    • Aug.
    • C. Xu, D. Tao, and C. Xu, "Large-margin multi-view information bottleneck", IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 8, pp. 1559-1572, Aug. 2014.
    • (2014) IEEE Trans. Pattern Anal. Mach. Intell. , vol.36 , Issue.8 , pp. 1559-1572
    • Xu, C.1    Tao, D.2    Xu, C.3
  • 56
    • 84884823170 scopus 로고    scopus 로고
    • Nonlocal hierarchical dictionary learning using wavelets for image denoising
    • Dec.
    • R. Yan, L. Shao, and Y. Liu, "Nonlocal hierarchical dictionary learning using wavelets for image denoising", IEEE Trans. Image Process., vol. 22, no. 12, pp. 4689-4698, Dec. 2013.
    • (2013) IEEE Trans. Image Process. , vol.22 , Issue.12 , pp. 4689-4698
    • Yan, R.1    Shao, L.2    Liu, Y.3
  • 57
  • 58
    • 84903266238 scopus 로고    scopus 로고
    • Learning object-to-class kernels for scene classification
    • Aug.
    • L. Zhang, X. Zhen, and L. Shao, "Learning object-to-class kernels for scene classification", IEEE Trans. Image Process., vol. 23, no. 8, pp. 3241-3253, Aug. 2014.
    • (2014) IEEE Trans. Image Process. , vol.23 , Issue.8 , pp. 3241-3253
    • Zhang, L.1    Zhen, X.2    Shao, L.3
  • 59
    • 79951751439 scopus 로고    scopus 로고
    • NESVM: A fast gradient method for support vector machines
    • Dec.
    • T. Zhou, D. Tao, and X. Wu, "NESVM: A fast gradient method for support vector machines", in Proc. IEEE 10th Int. Conf. Data Mining, Dec. 2010, pp. 679-688.
    • (2010) Proc. IEEE 10th Int. Conf. Data Mining , pp. 679-688
    • Zhou, T.1    Tao, D.2    Wu, X.3


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