Recognizing arabic handwritten characters using deep learning and genetic algorithms-Reference-Cited by-同舟云学术

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Published:2021-07-31 Issue:21-23 Volume:80 Page:32473-32509
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Balaha Hossam Magdy^ORCID,Ali Hesham Arafat,Youssef Esraa Khaled,Elsayed Asmaa Elsayed,Samak Reem Adel,Abdelhaleem Mohammed Samy,Tolba Mohammed Mosa,Shehata Mahmoud Ragab,Mahmoud Mahmoud Refa’at,Abdelhameed Mariam Mahmoud,Mohammed Mostafa Mahmoud

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-021-11185-4.pdf

Reference138 articles.

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2. Acharya S, Pant AK, Gyawali PK (2015) Deep learning based large scale handwritten devanagari character recognition. In: 2015 9th International conference on software, knowledge, information management and applications (SKIMA). IEEE, pp 1–6

3. Ahmed R et al (2020) Offline arabic handwriting recognition using deep machine learning: A review of recent advances. In: Ren J et al (eds) Advances in brain inspired cognitive systems. Springer International Publishing, Cham, pp 457–468

4. Akhand M, Ahmed M, Rahman MH (2016) Convolutional neural network based handwritten bengali and bengali-english mixed numeral recognition. Int J image Graph Signal Process 8(9):40

5. Al-Helali BM, Mahmoud SA (2017) Arabic online handwriting recognition (aohr): A survey. ACM Comput Surv 50(3)

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