@Article{2018.100000005,
AUTHOR = {Amin Alqudah, Hussein R. Al-Zoubi, Mahmood A. Al-Khassaweneh, Mohammed Al-Qodah},
TITLE = {Highly Accurate Recognition of Handwritten Arabic Decimal Numbers  Based on a Self-Organizing Maps Approach},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {3},
PAGES = {493--505},
URL = {http://www.techscience.com/iasc/v24n3/39775},
ISSN = {2326-005X},
ABSTRACT = {Handwritten numeral recognition is one of the most popular fields of research 
in automation because it is used in many applications. Indeed, automation 
has continually received substantial attention from researchers. Therefore, 
great efforts have been made to devise accurate recognition methods with 
high recognition ratios. In this paper, we propose a method for integrating 
the correlation coefficient with a Self-Organizing Maps (SOM)-based 
technique to recognize offline handwritten Arabic decimal digits. The 
simulation results show very high recognition rates compared with the rates 
achieved by other existing methods.},
DOI = {10.31209/2018.100000005}
}