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» Discriminative Bernoulli Mixture Models for Handwritten Digi...
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NIPS
1994
13 years 6 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
ICCV
2001
IEEE
14 years 6 months ago
Separating Appearance from Deformation
By representing images and image prototypes by linear subspaces spanned by "tangent vectors" (derivatives of an image with respect to translation, rotation, etc.), impre...
Nebojsa Jojic, Patrice Simard, Brendan J. Frey, Da...
DAGM
2009
Springer
13 years 11 months ago
Deformation-Aware Log-Linear Models
Abstract. In this paper, we present a novel deformation-aware discriminative model for handwritten digit recognition. Unlike previous approaches our model directly considers image ...
Tobias Gass, Thomas Deselaers, Hermann Ney
NIPS
1998
13 years 6 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
PAMI
1998
134views more  PAMI 1998»
13 years 4 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