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Journal ArticleDOI

Methods of combining multiple classifiers and their applications to handwriting recognition

Lei Xu, +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. >

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References
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Journal ArticleDOI

Computer recognition of totally unconstrained handwritten zip codes

TL;DR: The techniques, image processing together with recognition, described in this thesis present a complete model of an optical reader for ZIP code recognition.
Proceedings ArticleDOI

A blackboard-based approach to handwritten ZIP code recognition

TL;DR: A methodology for recognizing ZIP codes in handwritten addresses is presented that uses many diverse pattern recognition and image processing algorithms and takes the form of a blackboard architecture that opportunistically invokes routines as needed.
Journal ArticleDOI

Adaptive prediction for speech encoding

TL;DR: An overview of adaptive prediction in differential pulse code modulation systems used for speech encoding at 16 to 32 kilobits/sec.(kbps) is presented, and comparative performances results of several backward adaptive algorithms and predictor structures are discussed.
Journal ArticleDOI

Introduction to the Special Section

TL;DR: The paper by Liu and Fu clearly demonstrates the feasibility of the syntactic approach to teleseismic discrimination with comparable performance as the decision-theoretic approach in seismic analysis and classification.