Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1375
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dc.contributor.authorGamage, C.Y.-
dc.contributor.authorBogahawatte, J.R.M.-
dc.contributor.authorPrasadika, U.K.T.-
dc.contributor.authorSumathipala, S.-
dc.date.accessioned2022-02-23T09:05:54Z-
dc.date.available2022-02-23T09:05:54Z-
dc.date.issued2020-12-10-
dc.identifier.isbn978-1-7281-8412-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1375-
dc.description.abstractRecently researches have been conducted in the domain of currency recognition. The task of recognizing the currency notes has become challenging due to the distortion of the notes over time. Currency recognition systems in Sinhala for visually impaired people are rarely developed. To address this problem a research has been done and a relevant application has been implemented comprising three modules as Speech Recognition module, Currency Recognition module and Text to Speech Module. The major challenge in all three modules is to achieve a better accuracy using deep learning concepts. TensorFlow platform and Keras library were used to build the speech recognition neural network model for Sinhala spoken words. Deep learning neural networks were utilized for the development of currency recognition module and text to speech module.en_US
dc.language.isoenen_US
dc.publisher2020 2nd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.relation.ispartofseriesVol.1;-
dc.subjectCurrency Recognitionen_US
dc.subjectSinhala Speech Recognitionen_US
dc.subjectDeep Learning Neural Networken_US
dc.subjectTensorFlowen_US
dc.subjectFeature Extractionen_US
dc.subjectText to Speechen_US
dc.titleDNN Based Currency Recognition System for Visually Impaired in Sinhalaen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC51239.2020.9357295en_US
Appears in Collections:2nd International Conference on Advancements in Computing (ICAC) | 2020

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