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Recognition of Devanagari Characters Using Neural Networks
Kanad KEENI Hiroshi SHIMODAIRA Tetsuro NISHINO Yasuo TAN
IEICE TRANSACTIONS on Information and Systems
Publication Date: 1996/05/25
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Character Recognition and Document Understanding)
Category: Neural Networks
character recognition, neural networks, structure analysis, heuristic coding, feature vector, prototype vector,
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Devanagari is the most widely used script in India. Here, a method is introduced for recognizing Devanagari characters using Neural network. The proposed method reduces the number of output unit necessary for a conventional neural network where the classification is based on a winner take all basis. An automatic coding procedure for representing the output layer of the network and a different method for the final classification is also proposed. Along with the automatic coding procedure, a heuristic method for representing the output units by exploiting the structural information of Devanagari character is also demonstrated. Besides, it has been shown by random representation of the output layer that the representation effects the generalization/performance of the network. The proposed automatic representation gave the recognition rate of 98.09% for 44 categories.