Gibrael Abosamra*, Hadi Oqaibi
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1-28, 2021, DOI:10.32604/cmc.2021.015318
Abstract Even though much advancements have been achieved with regards to the recognition of handwritten characters, researchers still face difficulties with the handwritten character recognition problem, especially with the advent of new datasets like the Extended Modified National Institute of Standards and Technology dataset (EMNIST). The EMNIST dataset represents a challenge for both machine-learning and deep-learning techniques due to inter-class similarity and intra-class variability. Inter-class similarity exists because of the similarity between the shapes of certain characters in the dataset. The presence of intra-class variability is mainly due to different shapes written by different writers for the same character. In this… More >
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