Digital Text Authentication Using Deep Learning: Proposition for the Digital Quranic Text-Reference-Cited by-同舟云学术

Digital Text Authentication Using Deep Learning: Proposition for the Digital Quranic Text

Published:2022 Issue: Volume: Page:56-64
ISSN:2367-3370
Container-title:Artificial Intelligence and Its Applications
language:
Short-container-title:

Author:

Touati-Hamad Zineb,Laouar Mohamed Ridda^ORCID,Bendib Issam

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-96311-8_6

Reference28 articles.

1. Ahmed, H., Traore, I., Saad, S.: Detecting opinion spams and fake news using text classification. Secur. Priv. 1, e9 (2018)

2. Minaee, S., Kalchbrenner, N., Cambria, E., Nikzad, N., Chenaghlu, M., Gao, J.: Deep learning–based text classification: a comprehensive review. ACM Comput. Surv. CSUR 54, 1–40 (2021)

3. Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. ArXiv preprint arXiv:1810.04805 (2018)

4. Liu, X., He, P., Chen, W., Gao, J.: Multi-task deep neural networks for natural language understanding. ArXiv preprint arXiv:1901.11504 (2019)

5. Studies in Computational Intelligence;S Srinivasan,2021

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. UniHaCh: Unicode and Hash Function Supported with Counting and Frequency Recurrence of Arabic Characters for Quranic Text Watermarking;Arabian Journal for Science and Engineering;2023-11-17

2. A Secure Framework Design for Digital Sensitive Content Certification;12th International Conference on Information Systems and Advanced Technologies “ICISAT 2022”;2023