Recognition Of Handwritten Arabic Words With Dropout Applied In Mdlstm

Offline handwriting recognition is the ability to decode an intelligible handwritten input from paper documents into digitized format readable by machines. This field remains an on-going research problem especially for Arabic Script due to its cursive appearance, the variety of writers and the diversity of styles. In this paper we focus on the Intelligent Words Recognition system based on MDLSTM, on which a dropout technique is applied during training stage. This technique prevents our system against overfitting and improves the recognition rate. To evaluate our system we use IFN/ENIT database.