Abstract

paper presents the development of Gurumukhi character recognition system of isolated handwritten characters by using Neocognitron at the first time. Well- known neocognitron artificial neural network is chosen for its fast processing time and its good performance for pattern recognition problems. Here we have found the recognition accuracy of both learned and unlearned images of characters. Learned images have recognition accuracy as 91.77 % and unlearned images have recognition accuracy as 93.79 %. The overall recognition accuracy for both learned and unlearned Gurmukhi characters are 92.78 %. This confirms that the proposed neocognitron artificial neural network approach is suitable for the development of isolated handwritten characters of Gurumukhi script.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.