|Table of Contents|

Handwriting Chinese Text Recognition Using BiLSTM Network(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2019年03期
Page:
58-64
Research Field:
·全国机器学习会议论文专栏·
Publishing date:

Info

Title:
Handwriting Chinese Text Recognition Using BiLSTM Network
Author(s):
Zhang Xinfeng; Yan Kunpeng; Zhao Xun
Information Department,Beijing University of Technology,Beijing 100124,China
Keywords:
OCR; handwriting recognition; deep learning; LSTM neural network; CTC-Loss function
PACS:
TP391
DOI:
10.3969/j.issn.1001-4616.2019.03.008
Abstract:
Handwriting recognition is an active research topic in the domain of natural language processing(NLP)and computer vision(CV). Aiming at the problem of handwriting Chinese text recognition,this paper proposed a method using BiLSTM neural network. The method can be used to recognize Chinese text which writed carefully and neatly. Firstly,according to the student’s characteristics of handwriting,make normalized to the section of data. Then,use CNN network to extract image features and use LSTM network to record the context diagram. Finally use the CTC-Loss function to accelerate convergence in our data model. The results illustrate the effectivemess of the proposed method.

References:

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Last Update: 2019-09-30