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
Combining classifiers using nearest decision prototypes
TL;DR: A new classifier fusion method to combine soft-level classifiers with a new approach, which can be considered as a generalized decision templates method, which is evaluated over well-known classification datasets suggesting superiority of the method in comparison with other proposed techniques.
Proceedings ArticleDOI
Adaptive combination of classifiers and its application to handwritten Chinese character recognition
Baihua Xiao,C.H. Wang,Ruwei Dai +2 more
TL;DR: The experimental results demonstrate that this method can result in substantial improvement in overall performance and many existing integration schemes can be considered as special cases of the proposed method.
Proceedings ArticleDOI
Enhancing the performance of personal identity authentication systems by fusion of face verification experts
TL;DR: The behavior knowledge space fusion strategy achieved consistently better results than the decision templates method and exhibited quasi monotonic behavior as the number of experts combined increased, which means that the performance of the multimodal system is not degraded by adding experts.
Proceedings ArticleDOI
Multi-classifier framework for atlas-based image segmentation
TL;DR: It is concluded that multi-classifier methods have a natural application to atlas-based segmentation and the potential to increase classification accuracy in real-world segmentation problems.
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