@article{(Open Science Index):https://publications.waset.org/pdf/14126, title = {Bi-lingual Handwritten Character and Numeral Recognition using Multi-Dimensional Recurrent Neural Networks (MDRNN)}, author = {Kandarpa Kumar Sarma}, country = {}, institution = {}, abstract = {The key to the continued success of ANN depends, considerably, on the use of hybrid structures implemented on cooperative frame-works. Hybrid architectures provide the ability to the ANN to validate heterogeneous learning paradigms. This work describes the implementation of a set of Distributed and Hybrid ANN models for Character Recognition applied to Anglo-Assamese scripts. The objective is to describe the effectiveness of Hybrid ANN setups as innovative means of neural learning for an application like multilingual handwritten character and numeral recognition.}, journal = {International Journal of Electrical and Computer Engineering}, volume = {3}, number = {4}, year = {2009}, pages = {628 - 635}, ee = {https://publications.waset.org/pdf/14126}, url = {https://publications.waset.org/vol/28}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 28, 2009}, }