A SURVEY ON RECURRENT NEURAL NETWORK AND VARIOUS TECHNIQUES FOR HANDWRITTEN RECOGNITION |
Author(s): |
| Geetanjali Bhagwani , L.J. Institute of Engineering & Technology,Ahmedabad, Gujarat, India; Ompriya Kale, L.J. Institute of Engineering & Technology,Ahmedabad, Gujarat, India |
Keywords: |
| CTC Token Passing Algorithm, Recurrent Neural Network, Handwritten Recognition |
Abstract |
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At present large number of manuscripts, books, journals, and articles remain largely inaccessible in library archives. Keyword spotting refers to the process of retrieving all instances of a given keyword from these documents. In the present paper, a novel keyword spotting method for handwritten documents is0020obtained using different various systems for unconstrained handwritten recognition. A new technique is used for robust keyword spotting that uses bidirectional Long Short-Term Memory (BLSTM) recurrent neural nets and CTC Token Passing Algorithm to incorporate contextual information in documents. Each surveyed method briefly discusses the keyword searching issues and solutions. |
Other Details |
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Paper ID: IJSRDV2I9471 Published in: Volume : 2, Issue : 9 Publication Date: 01/12/2014 Page(s): 747-750 |
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