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» Using Random Forests for Handwritten Digit Recognition
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TFS
2008
174views more  TFS 2008»
13 years 5 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
ICPR
2004
IEEE
14 years 6 months ago
Off-line Handwritten Textline Recognition Using a Mixture of Natural and Synthetic Training Data
In this paper the problem of off-line handwritten cursive text recognition is considered. A method for expanding the set of available training textlines by applying random perturb...
Tamás Varga, Horst Bunke
NIPS
1994
13 years 7 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 6 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
ICDAR
2011
IEEE
12 years 5 months ago
Tuning between Exponential Functions and Zones for Membership Functions Selection in Voronoi-Based Zoning for Handwritten Charac
— In Handwritten Character Recognition, zoning is rigtly considered as one of the most effective feature extraction techniques. In the past, many zoning methods have been propose...
Sebastiano Impedovo, Giuseppe Pirlo