Detection of Optical Characters Using Text Structure Modeling

  • Authors

    • Miss Velantina Kapale
    • Prof. Mangesh Ghonge
    2018-07-07
    https://doi.org/10.14419/ijet.v7i3.8.15228
  • Text categorization, Back propagation, BPNN, Genetic algorithm, Neural network.

  • Abstract

    The basic use of back propagation(bp) neural network for textual content categorization and category in addition to type and could gather high everyday giant overall performance and accuracy. But, the high-quality drawback of this network is its prolonged training time. The genetic algorithm is regularly used to generate weights on network layer and beneficial for optimization. In proposed system we employ the mixture of each genetic set of rules and the returned propagation neural community for text categorization additionally the usage of the textual content structure we will understand the unique enter object through using characteristic extraction input item. We're able to use the genetic algorithm to reduce weights of edges within the but returned propagation neural community in used to backpropagating techniques. On the equal body, we are able to used to enhance the genetic algorithm to increase its performance and accuracy of neural network.

     

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  • How to Cite

    Velantina Kapale, M., & Mangesh Ghonge, P. (2018). Detection of Optical Characters Using Text Structure Modeling. International Journal of Engineering & Technology, 7(3.8), 92-96. https://doi.org/10.14419/ijet.v7i3.8.15228

    Received date: 2018-07-06

    Accepted date: 2018-07-06

    Published date: 2018-07-07