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A robust free size OCR for omni-font persian/arabic printed document using combined MLP/SVM

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2005) 3773 LNCS 601-610
DOI: 10.1007/11578079_63
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Abstract

Optical character recognition of cursive scripts present a number of challenging problems in both segmentation and recognition processes and this attracts many researches in the field of machine learning. This paper presents a novel approach based on a combination of MLP and SVM to design a trainable OCR for Persian/Arabic cursive documents. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Pirsiavash, H., Mehran, R., & Razzazi, F. (2005). A robust free size OCR for omni-font persian/arabic printed document using combined MLP/SVM. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3773 LNCS, pp. 601–610). https://doi.org/10.1007/11578079_63

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