2005
DOI: 10.1007/11579427_86
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An Efficient Hybrid Approach for Online Recognition of Handwritten Symbols

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Cited by 4 publications
(1 citation statement)
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“…Normally statistical recognizers are more reliable, however, they also have some disadvantages, it is very complex and computationally high to train and classify a large number of shapes because a large vocabulary is needed. The problems in fuzzy rules are lack of training and impossible to form exhaustive set of rules that can model all possibilities [26]. This paper describes a hybrid approach for the handwritten Urdu character recognition written in both Nasta'liq and Naskh styles.…”
Section: Introductionmentioning
confidence: 99%
“…Normally statistical recognizers are more reliable, however, they also have some disadvantages, it is very complex and computationally high to train and classify a large number of shapes because a large vocabulary is needed. The problems in fuzzy rules are lack of training and impossible to form exhaustive set of rules that can model all possibilities [26]. This paper describes a hybrid approach for the handwritten Urdu character recognition written in both Nasta'liq and Naskh styles.…”
Section: Introductionmentioning
confidence: 99%