(University of Eloued جامعة الوادي, 2022-01-24) KORICHI, Aicha; SLATNIA, Sihem; TAGOUGUI, Najiba; ZOUARI, Ramzi; KHERALLAH, Monji; AIADI, Oussama
Currently, deep learning techniques have become the core of recent research in pattern recognition
domain and especially for the handwriting recognition field where the challenges for the Arabic language are
stilling. Despite their high importance and performances, for the best of our acknowledge, deep learning
techniques have not been investigated in the context of Arabic handwritten literal amount recognition. The
main aim of this paper is to investigate the effect of several Convolutional Neural Networks CNNs based on the
proposed architecture with regularization parameters for such context. To achieve this aim, the AHDB database
was used where very promising results were obtained outperforming the previous works on this database.
