Contribution of recurrent connectionist language models in improving LSTM-based Arabic text recognition in videos

Unconstrained text recognition in videos is a very challenging task that begins to draw the attention of the OCR community. However, for Arabic video contents, this problem is much less addressed compared at least with Latin script. This work presents our latest contribution to this task, introducin...

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Bibliographic Details
Published in:	Pattern recognition Vol. 64; pp. 245 - 254
Main Authors:	Yousfi, Sonia, Berrani, Sid-Ahmed, Garcia, Christophe
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.04.2017 Elsevier
Subjects:	Arabic video OCR Artificial Intelligence Computer Science Computer Vision and Pattern Recognition Connectionist language model Convolutional Neural Network Decoding Document and Text Processing Image Processing LSTM Machine Learning Multimedia Neural and Evolutionary Computing RNN Signal and Image Processing Convolutional Neural Network Arabic video OCR Connectionist language model RNN LSTM Decoding
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
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