Journal ArticleDOI
Methods of combining multiple classifiers and their applications to handwriting recognition
Lei Xu,Adam Krzyżak,Ching Y. Suen +2 more
- Vol. 22, Iss: 3, pp 418-435
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TLDR
On applying these methods to combine several classifiers for recognizing totally unconstrained handwritten numerals, the experimental results show that the performance of individual classifiers can be improved significantly.Abstract:
Possible solutions to the problem of combining classifiers can be divided into three categories according to the levels of information available from the various classifiers. Four approaches based on different methodologies are proposed for solving this problem. One is suitable for combining individual classifiers such as Bayesian, k-nearest-neighbor, and various distance classifiers. The other three could be used for combining any kind of individual classifiers. On applying these methods to combine several classifiers for recognizing totally unconstrained handwritten numerals, the experimental results show that the performance of individual classifiers can be improved significantly. For example, on the US zipcode database, 98.9% recognition with 0.90% substitution and 0.2% rejection can be obtained, as well as high reliability with 95% recognition, 0% substitution, and 5% rejection. >read more
Citations
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Journal ArticleDOI
Similarity learning for texture image retrieval using multiple classifier system
TL;DR: A texture image retrieval system is developed that learns the visual similarity in terms of class membership using multiple classifiers and achieves higher retrieval accuracy with lower standard deviation compared to all the competing methods irrespective of the texture database and feature set used.
Proceedings ArticleDOI
Digital staining of pathological tissue specimens using spectral transmittance
TL;DR: Initial results of the experiments show the viability of multispectral imaging (MSI) for the implementation of digital staining in the pathological context for transformation of a Hematoxylin and Eosin stained specimen to its Masson-Trichrome stained counterpart.
Decision Templates with Gradient based Features for Farsi Handwritten Word Recognition
TL;DR: A set of experiments were conducted to compare Decision Templates with some combination rules and results show that template based fusion method is superior to the other schemes.
Proceedings ArticleDOI
Large-set handwritten character recognition with multiple stochastic models
H.-S. Park,Seong-Whan Lee +1 more
TL;DR: An efficient recognition scheme for large-set handwritten characters is proposed in the framework of multiple stochastic models, in this case, first order hidden Markov models which can model stochastically the input pattern with numerous variations.
Proceedings ArticleDOI
Benefit of multiclassifier systems for Arabic handwritten words recognition
TL;DR: Two types of features are fed to a number of artificial neural networks (ANN) and their respective responses are combined for the recognition of handwritten Arabic literal words.
References
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Book
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Book
A mathematical theory of evidence
TL;DR: This book develops an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions.
Journal ArticleDOI
Statistical and structural approaches to texture
TL;DR: This survey reviews the image processing literature on the various approaches and models investigators have used for texture, including statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models.
Journal ArticleDOI
An introduction to hidden Markov models
TL;DR: The purpose of this tutorial paper is to give an introduction to the theory of Markov models, and to illustrate how they have been applied to problems in speech recognition.