Bi-Lingual Handwritten Character And Numeral Recognition Using Multi-Dimensional Recurrent Neural Networks (Mdrnn)
Kandarpa Kumar Sarma · Zenodo (CERN European Organization for Nuclear Research) · 2009
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.