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IJON
2011
186views more  IJON 2011»
12 years 7 months ago
Discriminative structure selection method of Gaussian Mixture Models with its application to handwritten digit recognition
, Yunde Jia Model structure selection is currently an open problem in modeling data via Gaussian Mixture Models (GMM). This paper proposes a discriminative method to select GMM st...
Xuefeng Chen, Xiabi Liu, Yunde Jia
ICDAR
2009
IEEE
13 years 11 months ago
Unsupervised Selection and Discriminative Estimation of Orthogonal Gaussian Mixture Models for Handwritten Digit Recognition
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
Xuefeng Chen, Xiabi Liu, Yunde Jia
TFS
2008
174views more  TFS 2008»
13 years 4 months ago
Type-2 Fuzzy Markov Random Fields and Their Application to Handwritten Chinese Character Recognition
In this paper, we integrate type-2 (T2) fuzzy sets with Markov random fields (MRFs) referred to as T2 FMRFs, which may handle both fuzziness and randomness in the structural patter...
Jia Zeng, Zhi-Qiang Liu
NIPS
1998
13 years 5 months ago
Making Templates Rotationally Invariant. An Application to Rotated Digit Recognition
This paper describes a simple and efficient method to make template-based object classification invariant to in-plane rotations. The task is divided into two parts: orientation di...
Shumeet Baluja
ICASSP
2011
IEEE
12 years 8 months ago
Maximum margin structure learning of Bayesian network classifiers
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
Franz Pernkop, Michael Wohlmay, Manfred Mücke