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dc.contributor.author Rabby, AKM Shahariar Azad
dc.contributor.author Hossain, Syed Akhter
dc.contributor.author Abujar, Sheikh
dc.contributor.author Islam, Md. Sanzidul
dc.contributor.author Haque, Sadeka
dc.date.accessioned 2022-02-06T09:28:51Z
dc.date.available 2022-02-06T09:28:51Z
dc.date.issued 2019-07-17
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7001
dc.description.abstract Ekush the largest dataset of handwritten Bangla characters for research on handwritten Bangla character recognition. In recent years Machine learning and deep learning application-based researchers have achieved interest and one of the most significant application is handwritten recognition. Because it has the tremendous application such in Bangla OCR. Also, Bangla writing script is one of the most popular in the world. For that reason, we are introducing a multipurpose comprehensive dataset for Bangla Handwritten Characters. The proposed dataset contains Bangla modifiers, vowels, consonants, compound letters and numerical digits that consists of 367,018 isolated handwritten characters written by 3086 unique writers which were collected within Bangladesh. This dataset can be used for other problems i.e.: gender, age, district base handwritten related research, because the samples were collected include verity of the district, age group and the equal number of male and female. It is intended to fabricate acknowledgment technique for hand written Bangla characters. This dataset is unreservedly accessible for any sort of scholarly research work. The Ekush dataset is trained and validated with Ekush Net and indicated attractive acknowledgment precision 97.73% for Ekush dataset, which is up until this point, the best exactness for Bangla character acknowledgment. The Ekush dataset and relevant code can be found at this link: https://github.com/ShahariarRabby/ekush. en_US
dc.language.iso en_US en_US
dc.publisher Communications in Computer and Information Science, Springer en_US
dc.subject Bangla handwritten en_US
dc.subject Data science en_US
dc.subject Machine learning en_US
dc.subject Deep learning en_US
dc.subject Computer vision en_US
dc.subject Pattern recognition en_US
dc.title Ekush en_US
dc.title.alternative a Multipurpose and Multitype Comprehensive Database for Online Off-line Bangla Handwritten Characters en_US
dc.type Article en_US


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