Abstract
We have newly developed a handwritten numeric character recognition system with neural networks based on an approximate reasoning architecture (NARA). Handwritten character recognition is one of the most difficult tasks in an area of pattern recognition because of the variation of handwritten images even in a same category of character. NARA, which consists of a classifier of input data, several sub-neural networks and an integrator of the outputs of sub-neural networks can realize a stable recognition of large variations of handwritten character images, and achieved a correct answer rate of 95.41%, an error rate of 0.20% and a rejection rate of 4.38%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
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.