Uncertainty Management in Expert Systems
IEEE Expert: Intelligent Systems and Their Applications
Recognition of Handprinted Bangla Numerals Using Neural Network Models
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
A hierarchical approach to recognition of handwritten Bangla characters
Pattern Recognition
Recognition of Numeric Postal Codes from Multi-script Postal Address Blocks
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
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The work presents an application of Dempster-Shafer (DS) technique for combination of classification decisions obtained from two Multi Layer Perceptron (MLP) based classifiers for optical character recognition (OCR) of handwritten Bangla digits using two different feature sets. Bangla is the second most popular script in the Indian subcontinent and the fifth most popular language in the world. The two feature sets used for the work are so designed that they can supply complementary information, at least to some extent, about the classes of digit patterns to the MLP classifiers. On experimentation with a database of 6000 samples, the technique is found to improve recognition performances by a minimum of 1.2% and a maximum of 2.32% compared to the average recognition rate of the individual MLP classifiers after 3-fold cross validation of results. The overall recognition rate as observed for the same is 95.1% on average.