A Hybrid RNN Model for Cursive Offline Handwriting Recognition

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.