Segmentation Technique For The Learning In Recognition Of The Two Handwritten Bangla Digits Using Counterpropagation Neural Network | Zendy

Abul Haque | Zendy; Afsaneh Minaie | Zendy

Open Access

Segmentation Technique For The Learning In Recognition Of The Two Handwritten Bangla Digits Using Counterpropagation Neural Network

Author(s) -

Abul Haque,

Afsaneh Minaie

Publication year - 2020

Language(s) - English

Resource type - Conference proceedings

DOI - 10.18260/1-2--14338

Subject(s) - bengali , artificial intelligence , computer science , artificial neural network , deep learning , character recognition , character (mathematics) , segmentation , feature extraction , natural language processing , numeral system , speech recognition , feature (linguistics) , field (mathematics) , optical character recognition , pattern recognition (psychology) , image (mathematics) , mathematics , linguistics , philosophy , geometry , pure mathematics

We are proposing a segmentation technique for the learning of the two Bangla digits incorporating the grid method, the regional search method, the feature extraction method, and the counterpropagation neural network. We emphasized the recognition of the two Bangla digits one and nine since these two digits look similar. The experimental result shows an overall increased rate of recognition for Bangla one and nine.

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