@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},