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ICDAR
2003
IEEE

A Neural-Evolutionary Approach for Feature and Architecture Selection in Online Handwriting Recognition

11 years 5 months ago
A Neural-Evolutionary Approach for Feature and Architecture Selection in Online Handwriting Recognition
An automatic recognition of online handwritten text has been an on-going research problem for nearly four decades. It has been gaining more interest due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. However for these input modalities to be economical and user friendly the recognition rate should be very high for real time use. Also, the large number of writing styles and the variability between them makes the handwriting recognition problem a very challenging area for researchers. Many researchers have proposed a number of novel techniques for online handwriting recognition. However, an acceptable classification rate has not been achieved yet and there is a lack of techniques, which can find appropriate features, architecture and network parameters for online handwriting recognition. In this paper we propose a novel neurogenetic technique to improve classification accuracy through the selection of appropriate features and network ...
Brijesh Verma, Moumita Ghosh
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ICDAR
Authors Brijesh Verma, Moumita Ghosh
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