H. Tenmoto, M. Kudo, and M. Shimbo, "Mdl-based selection of the number of components in mixture models for pattern recognition," in Proc. of SSPR/SPR, 1998, pp. 831--836. Home/Search Document Details and Download
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Higher-Order Dependencies in Local Appearance Models - Guillamet, Moghaddam.. (2003) (Correct)
....de la Generalitat de Catalunya and Ministerio de Ciencia y Tecnologia grant TIC2000 0399 C02 01. joint probability densities which can model high order dependencies. In order to model the tuple space, we use an adaptative Gaussian mixture model based on the Minimum Description Length (MDL)[8] criterion to properly estimate our probability densities. We have tested our method in a closed environment where we detect real objects with different configurations, poses and levels of occlusions. Our technique is however able to manage with real, complex and cluttered environments and we ....
H. Tenmoto, M. Kudo, and M. Shimbo, "Mdl-based selection of the number of components in mixture models for pattern recognition," in Proc. of SSPR/SPR, 1998, pp. 831--836.
Number of Components and Initialization in Gaussian Mixture .. - Paclík, Novovicová (Correct)
....and by the nonlinear numerical opti mization method. There have also been published other approaches for the estimation of the number of components arising from the mixture model. For example Celeux and Soromenho [1] published method based on normalized entropy criterion (NEC) and Tenmoro et al. [9] suggested to use Minimum Description Length (MDL) criterion for the same purpose. Mixture initialization is random in the first case and based on fuzzy c means method in the sec ond one. Grim et al. 4] proposed a method starting with optimally smoothed kernel estimate which is subsequently ....
H. Tenmoro, M. Kudo, and M. Shimbo. MDL-Based Selection of the Number of Components in Mixture Models for Pattern Recognition. In Lecture Notes in Computer Science 1451: Advances in Pattern Recognition, pages 831 836, 1998.
MDL Principle for Robust Vector Quantization - Bischof, Leonardis, Selb (1999) (3 citations) (Correct)
....to find the 1 Where the breakdown point of an estimator is determined by the smallest portion of outliers in the data set at which the estimation procedure can produce an arbitrarily wrong estimate [7, 8] 4 size of the network, but to determine a suitable encoding of the data. Tenmoto et al. [20] used MDL for the selection of the number of components for Gaussian Mixture Models, however, they used the approach for supervised learning and they did not consider outliers. Our approach differs from these methods; namely we use the MDL principle as a pruning criterion in an integral scheme and ....
H. Tenmoto, M. Kudo, and M. Shimbo. MDL-Based selection of the number of components in mixture models for pattern classification. In A. Amin, D. Dori, P. Pudil, and H. Freeman, editors, Advances in Pattern Recognition, number 1451 in Lecture Notes in Computer Science, pages 831--836. Springer, 1998.
Mitsubishi Electric Research Laboratories - Http Www Merl (2003) (Correct)
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H. Tenmoto, M. Kudo, and M. Shimbo, "Mdl-based selection of the number of components in mixture models for pattern recognition," in Proc. of SSPR/SPR, 1998, pp. 831--836.
Mitsubishi Electric Research Laboratories - Http Www Merl (2003) (Correct)
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H. Tenmoto, M. Kudo and M. Shimbo. MDL-Based Selection of the Number of Components in Mixture Models for Pattern Recognition. In SSPR/SPR, pp. 831-836, 1998.
Mitsubishi Electric Research Laboratories - Http Www Merl (2003) (Correct)
No context found.
H. Tenmoto, M. Kudo and M. Shimbo. MDL-Based Selection of the Number of Components in Mixture Models for Pattern Recognition. In SSPR/SPR, pp. 831-836, 1998.
Evidence Accumulation Clustering based on the K-Means Algorithm - Fred, Jain (2002) (1 citation) (Correct)
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H. Tenmoto, M. Kudo, and M. Shimbo. MDL-based selection of the number of components in mixture models for pattern recognition. In Adnan Amin, Dov Dori, Pavel Pudil, and Herbert Freeman, editors, Advances in Pattern Recognition, volume 1451 of Lecture Notes in Computer Science, pages 831--836. Springer Verlag, 1998.
Higher-Order Dependencies in Local Appearance Models - Guillamet, Moghaddam, Vitria (2003) (Correct)
No context found.
H. Tenmoto, M. Kudo, and M. Shimbo, "Mdl-based selection of the number of components in mixture models for pattern recognition," in Proc. of SSPR/SPR, 1998, pp. 831--836.
Local Apearance-Based Models using High-Order.. - Moghaddam, Guillamet, .. (2003) (1 citation) (Correct)
No context found.
H. Tenmoto, M. Kudo and M. Shimbo. MDL-Based Selection of the Number of Components in Mixture Models for Pattern Recognition. In SSPR/SPR, pp. 831-836, 1998.
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