In this paper we introduce Convolutional Neural Network (CNN) based method for Amharic character image recognition. We also introduce a dataset for training purposes. The proposed method has less pre-processing steps and out performs the state-of-the-art by a large margin. Experiments were done on 80,000 Amharic character images which was generated with different degradation level. We systematically evaluated the performance of the recognition model and achieved the state-of- art performance with an average recognition accuracy of 92.71%.
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Belay et al. (2018) studied this question.
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