Sardar Hasen Ali*, Maiwan Bahjat Abdulrazzaq
CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 429-448, 2024, DOI:10.32604/cmc.2024.048356
Abstract Handwritten character recognition (HCR) involves identifying characters in images, documents, and various sources such as forms surveys, questionnaires, and signatures, and transforming them into a machine-readable format for subsequent processing. Successfully recognizing complex and intricately shaped handwritten characters remains a significant obstacle. The use of convolutional neural network (CNN) in recent developments has notably advanced HCR, leveraging the ability to extract discriminative features from extensive sets of raw data. Because of the absence of pre-existing datasets in the Kurdish language, we created a Kurdish handwritten dataset called (KurdSet). The dataset consists of Kurdish characters, digits, texts, and symbols. The dataset… More >
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