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
Discriminant Independent Component Analysis
TL;DR: Experimental results show improved classification performance when dICA features are used for recognition tasks in comparison to unsupervised (principal component analysis and ICA) and supervised feature extraction techniques like linear discriminant analysis (LDA), conditional ICA, and those based on information theoretic learning approaches.
Proceedings ArticleDOI
Phase contrast image segmentation by weak watershed transform assembly
TL;DR: The present paper promotes the use of an assembly of marked watershed transforms, in order to increase the segmentation robustness, and results in the definition of candidate segmentations margins (expressed in terms of object border confidence) from which final segmentation can be chosen by means of thresholding.
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A decision fusion method based on multiple support vector machine system for fusion of hyperspectral and LIDAR data
TL;DR: The proposed method applied a support vector machine (SVM)-based classifier fusion system for fusion of hyperspectral and LIDAR data in the decision level and improved the classification accuracy and kappa coefficient in comparison to the single data sets.
Journal ArticleDOI
Incremental class learning approach and its application to handwritten digit recognition
Jacek Mańdziuk,Lokendra Shastri +1 more
TL;DR: Incremental Class Learning (ICL) as mentioned in this paper is a scalable learning approach for multi-class classification problems, which focuses on learning subproblems incrementally, one at a time, using the results of prior learning for subsequent learning.
Journal ArticleDOI
Sketch recognition by fusion of temporal and image-based features
TL;DR: These results are the first to confirm the complementary nature of image-based and temporal recognition methods for full sketch recognition, which has long been suggested, but never supported by data.
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