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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Proceedings ArticleDOI
Segmentation of numeric strings
TL;DR: This paper presents a complete procedure for the segmentation of handwritten numeric strings in which multiple segmentation algorithms based on contiguous row partition work sequentially on the binary image until an acceptable segmentation is obtained.
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Multi-classifier framework for atlas-based image segmentation
TL;DR: It is concluded that multi-classifier techniques have a natural application to atlas-based segmentation and increase classification accuracy in real-world segmentation problems.
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Dynamic classifier selection for effective mining from noisy data streams
TL;DR: A dynamic classifier selection (DCS) mechanism to integrate base classifiers for effective mining from data streams that dynamically selects a single "best" classifier to classify each test instance at run time is proposed.
Proceedings ArticleDOI
Emotion Detection From Infant Facial Expressions And Cries
TL;DR: A new system for translating the infant cries from its facial image and cry sounds is presented and uses k-means clustering to derive the reason why the infant is crying.
Proceedings ArticleDOI
Toward a combination rule to deal with partial conflict and specificity in belief functions theory
Arnaud Martin,Christophe Osswald +1 more
TL;DR: In this article, a mixed conjunctive and disjunctive rule, a generalization of conflict repartition rules, and a combination of these two rules are presented and discussed, and the authors propose a mixed combination rule following the proportional conflict redistribution rule modified by a discounting procedure.
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