High Performance Urdu and Arabic Video Text Recognition Using Convolutional Recurrent Neural Networks-Reference-Cited by-同舟云学术

High Performance Urdu and Arabic Video Text Recognition Using Convolutional Recurrent Neural Networks

Published:2021 Issue: Volume: Page:336-352
ISSN:0302-9743
Container-title:Document Analysis and Recognition – ICDAR 2021 Workshops
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Author:

Rehman Abdul,Ul-Hasan Adnan,Shafait Faisal

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-86198-8_24

Reference21 articles.

1. Competition on superimposed text detection and recognition in Arabic news video frames. https://diuf.unifr.ch/main/diva/AcTiVComp/index.html. Accessed 23 Feb 2021

2. Detect text in images | cloud vision API | google cloud. https://cloud.google.com/vision/docs/ocr. Accessed 26 May 2021

3. Ahmad, I., Wang, X., Li, R., Ahmed, M., Ullah, R.: Line and ligature segmentation of Urdu Nastaleeq text. IEEE Access 5, 1–17 (2017)

4. Al-Wzwazy, H.: Handwritten digit recognition using convolutional neural networks. Int. J. Innovative Res. Comput. Commun. Eng. 4, 1101–1106 (2016)

5. Bengio, Y., Simard, P., Frasconi, P.: Learning long-term dependencies with gradient descent is difficult. IEEE Trans. Neural Netw. Publ. IEEE Neural Netw. Council 5, 157–66 (1994)

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