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• W2048395523 abstract "This paper presents an approach to handwriting character recognition using recurrent neural networks. The method Multi-dimensional Recurrent Neural Network is evaluated against the classical techniques. To improve the model performance we propose the use of specialized Support Vector Machine combined with the original MDRNN in cases of confusion letters to avoid misclassifications. The performance of the method is verified in the C-Cube database and compared with different classifiers. The hierarchical combination presented promising results." @default.
• W2048395523 created "2016-06-24" @default.
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• W2048395523 date "2012-10-01" @default.
• W2048395523 modified "2023-10-18" @default.
• W2048395523 title "A Hybrid RNN Model for Cursive Offline Handwriting Recognition" @default.
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• W2048395523 doi "https://doi.org/10.1109/sbrn.2012.41" @default.
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