Abstract
The metasynthetic approach for solving complicated problems was proposed in 1990.1 And the characteristics of metasynthetic approach can be summarized as human-machine cooperation and integration. Directed by the idea of metasynthesis, the design of two kinds of handwritten Chinese character recognition systems are given in this article. All the designs focus on incorporating human knowledge into multiple classifier combination, which is different from conventional integration. The first one is multi-stage adaptive weighted multiple classifier combination, in which a neural network for coefficient predicting is trained by supervised learning to provide weights suitable for the input pattern. And the second scheme is based on totally parallel combination, in which human intelligence and computer capabilities are combined together through multi-step supervised learning. The experimental results demonstrate substantial improvement in overall performance for handwritten Chinese character recognition with thousands of classes that must be discriminated.
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 callMore From: International Journal of Information Technology & Decision Making
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.
