In this paper, we investigate a range of strategies for combining multiple machine learning techniques for recognizing Arabic characters, where we are faced with imperfect and dimensionally variable input characters. Experimental results show that combined confidence-based backoff strategies can produce more accurate results than each technique produces by itself and even the ones exhibited by the majority voting combination.
['Maytham Alabbas', 'Raidah S. Khudeyer', 'Sardar Jaf']
Improved Arabic characters recognition by combining multiple machine learning classifiers