TITLE:
Ensemble Neural Network in Classifying Handwritten Arabic Numerals
AUTHORS:
Kathirvalavakumar Thangairulappan, Palaniappan Rathinasamy
KEYWORDS:
Handwritten Numerals, Divide and Conquer, Cluster, Leader Algorithm, Neural Network, Ensemble, Classification
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.8 No.1,
December
28,
2015
ABSTRACT: 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 recognize the
patterns by Divide and Conquer approach using proposed ensemble neural network.
Experimental results show that the proposed method recognize the patterns
accurately.