Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes | Zendy

Youssef Boulid | Zendy; Abdelghani Souhar | Zendy; Mohamed Youss Elkettani | Zendy

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Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes

Author(s) -

Youssef Boulid,

Abdelghani Souhar,

Mohamed Youss Elkettani

Publication year - 2016

Publication title -

international journal of interactive multimedia and artificial intelligence

Language(s) - English

Resource type - Journals

ISSN - 1989-1660

DOI - 10.9781/ijimai.2016.416

Subject(s) - computer science , arabic , natural language processing , artificial intelligence , hidden markov model , pattern recognition (psychology) , linguistics , philosophy

The multilayer perceptron has a large wide of classification and regression applications in many fields: pattern recognition, voice and classification problems. But the architecture choice has a great impact on the convergence of these networks. In the present paper we introduce a new approach to optimize the network architecture, for solving the obtained model we use the genetic algorithm and we train the network with a back-propagation algorithm. The numerical results assess the effectiveness of the theoretical results shown in this paper, and the advantages of the new modeling compared to the previous model in the literature

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