@Article{2018.100000005, AUTHOR = {Amin Alqudah, Hussein R. Al-Zoubi, Mahmood A. Al-Khassaweneh,3, 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} }