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Ensemble Neural Network in Classifying Handwritten Arabic Numerals
2016
Journal of Intelligent Learning Systems and Applications
A method has been proposed to classify handwritten Arabic numerals in its compressed form using partitioning approach, Leader algorithm and Neural network. Handwritten numerals are represented in a matrix form. Compressing the matrix representation by merging adjacent pair of rows using logical OR operation reduces its size in half. Considering each row as a partitioned portion, clusters are formed for same partition of same digit separately. Leaders of clusters of partitions are used to
doi:10.4236/jilsa.2016.81001
fatcat:gnozcdsnfjg4zdxrmsnr6jztf4