Neural Network System for Continuous Handwritten Word Recognition

Discussion in 'Computers' started by Neilla Harez, Jun 24, 2021.

  1. Neilla Harez

    Neilla Harez Newbie

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    A continuous handwritten word recognition method is derived when the word is segmented into triplets (containing three letters). Two subsequent triplets have two common letters. The biggest challenge for recognition systems is to perform operations on a continuous word. In this, each word is subdivided into triplets, each containing three letters. Two neighbour triplets always contain two common letters, which represent the overlapping between letters. This kind of overlapping results is a higher recognition rate.

    Before the intelligent data capture software was available, the only option to digitize printed paper documents was to manually re-type the text. Not only was this massively time consuming, but it also came with typing errors.
    Intelligent document processing software is often used as a hidden or silent technology, powering many well-known systems and services in our daily life. It’s used in data entry automation, indexing documents for search engines, automatic number plate recognition, and assisting blind and visually impaired people.
     

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