Bangla Handwritten Character & Digit Recognition Using Convolutional Neural Network
| dc.contributor.author | TANVIR HOSSAIN | |
| dc.date.accessioned | 2025-11-23T07:53:00Z | |
| dc.date.available | 2025-11-23T07:53:00Z | |
| dc.date.issued | 2021-10-29 | |
| dc.description.abstract | Bangla handwriting recognition is an important and quite popular for the last few years. This paper proposes a Convolutional Neural Network(CNN) model to recognize the Bangla Handwritten Characters and Digits which contains 50 Character Classes and 10 Digit Classes. The most challenging part is to reduce the noise because of the different shapes of Banlga characters and digits. We propose to use a reliable and large dataset to get the best accuracy output with our proposed Convolutional Neural Network(CNN) model. We also compare the accuracy with the existing model. Finally, we hope we will make a model with less error and the best output result. | |
| dc.identifier.uri | https://dspace.nstu.ac.bd/handle/123456789/160 | |
| dc.title | Bangla Handwritten Character & Digit Recognition Using Convolutional Neural Network |
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