Efficient CRNN: Towards end-to-end low resource Urdu text recognition using depthwise separable convolutions and gated recurrent units-Reference-Cited by-同舟云学术

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Efficient CRNN: Towards end-to-end low resource Urdu text recognition using depthwise separable convolutions and gated recurrent units

Published:2024-01 Issue:1 Volume:61 Page:103544
ISSN:0306-4573
Container-title:Information Processing & Management
language:en
Short-container-title:Information Processing & Management

Author:

Nasir Tayyab^ORCID,Malik Muhammad Kamran

Publisher

Elsevier BV

Subject

Library and Information Sciences,Management Science and Operations Research,Computer Science Applications,Media Technology,Information Systems

Reference137 articles.

1. Urdu nastaleeq optical character recognition;Ahmad,2007

2. Offline Urdu Nastaleeq optical character recognition based on stacked denoising autoencoder;Ahmad;China Communications,2017

3. Improving Urdu recognition using character-based artistic features of nastalique calligraphy;Akram;IEEE Access,2019

4. Akram, Q., Hussain, S., Adeeba, F., Rehman, S., & Saeed, M. (2014). Framework of Urdu Nastalique optical character recognition system. In Proc. conf. lang. and technol.(CLT 14) (pp. 23–30).

5. UOCR: A ligature based approach for an Urdu OCR system;Ali,2016

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