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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

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

Paper ID: IJSRDV2I9471
Published in: Volume : 2, Issue : 9
Publication Date: 01/12/2014
Page(s): 747-750

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