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- W2888514770 abstract "In this paper, we present a deep learning model to recognize the handwritten Devanagari characters, which is the most popular language in India. This model aims to use the deep convolutional neural networks (DCNN) to eliminate the feature extraction process and the extraction process with the automated feature learning by the deep convolutional neural networks. It also aims to use the different optimizers with deep learning where the deep convolution neural network was trained with different optimizers to observe their role in the enhancement of recognition rate. It is discerned that the proposed model gives a 96.00% recognition accuracy with fifty epochs. The proposed model was trained on the standard handwritten Devanagari characters dataset." @default.
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- W2888514770 date "2018-08-23" @default.
- W2888514770 modified "2023-10-16" @default.
- W2888514770 title "Deep ConvNet with Different Stochastic Optimizations for Handwritten Devanagari Character" @default.
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- W2888514770 doi "https://doi.org/10.1007/978-981-13-0341-8_5" @default.
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