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ICDAR
2009
IEEE
14 years 2 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
ICPR
2002
IEEE
14 years 8 months ago
The Economics of Classification: Error vs. Complexity
Although usually classifier error is the main concern in publications, in real applications classifier evaluation complexity may play a large role as well. In this paper, a simple...
Dick de Ridder, Elzbieta Pekalska, Robert P. W. Du...
PAMI
1998
134views more  PAMI 1998»
13 years 7 months ago
A Bayesian Framework for Deformable Pattern Recognition With Application to Handwritten Character Recognition
—Deformable models have recently been proposed for many pattern recognition applications due to their ability to handle large shape variations.These proposed approaches represent...
Kwok-Wai Cheung, Dit-Yan Yeung, Roland T. Chin
NIPS
2001
13 years 8 months ago
Thin Junction Trees
We present an algorithm that induces a class of models with thin junction trees--models that are characterized by an upper bound on the size of the maximal cliques of their triang...
Francis R. Bach, Michael I. Jordan
NIPS
1994
13 years 8 months ago
Recognizing Handwritten Digits Using Mixtures of Linear Models
We construct a mixture of locally linear generative models of a collection of pixel-based images of digits, and use them for recognition. Different models of a given digit are use...
Geoffrey E. Hinton, Michael Revow, Peter Dayan