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NIPS
1994
13 years 5 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
ICPR
2004
IEEE
14 years 5 months ago
Bernoulli Mixture Models for Binary Images
Mixture modelling is a hot area in pattern recognition. Although most research in this area has focused on mixtures for continuous data, there are many pattern recognition tasks f...
Alfons Juan, Enrique Vidal
NIPS
2000
13 years 5 months ago
Recognizing Hand-written Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a non-linear generative model of handwritten images of digits. The q...
Guy Mayraz, Geoffrey E. Hinton
PAMI
2002
112views more  PAMI 2002»
13 years 4 months ago
Recognizing Handwritten Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a nonlinear generative model of handwritten images of digits. The qua...
Guy Mayraz, Geoffrey E. Hinton
ICDAR
2003
IEEE
13 years 9 months ago
Optimizing the Number of States, Training Iterations and Gaussians in an HMM-based Handwritten Word Recognizer
In off-line handwriting recognition, classifiers based on hidden Markov models (HMMs) have become very popular. However, while there exist well-established training algorithms, s...
Simon Günter, Horst Bunke