Machine learning and non-machine learning methods in mathematical recognition systems: Two decades’ systematic literature review-Reference-Cited by-同舟云学术

Machine learning and non-machine learning methods in mathematical recognition systems: Two decades’ systematic literature review

Published:2023-08-23 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Sakshi ^ORCID,Kukreja Vinay^ORCID

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/s11042-023-16356-z.pdf

Reference222 articles.

1. Afshan N, Afshar Alam M, Ali Mehdi S (2017) An Analysis of Mathematical Expression Recognition Techniques. Int J Adv Res Comput Sci 8(5):2021–2026 www.ijarcs.info

2. Aggarwal R, Harit G, Tiwari A (2020) Structural analysis of offline handwritten mathematical expressions. Proceedings of 3rd International Conference on Computer Vision and Image Processing. (Springer, Singapore) 1024:213–225

3. Ahmed M, Ward R, Kharma N (2004) Solving mathematical problems using knowledge-based systems. Math Comput Simul 67(1–2):149–161. https://doi.org/10.1016/j.matcom.2004.05.015

4. Ali A, Gravino C (2019) A systematic literature review of software effort prediction using machine learning methods. Journal of Software: Evolution and Process 31(10):1–25. https://doi.org/10.1002/smr.2211

5. Alvaro F (2015) Mathematical expression recognition based on probabilistic grammars [Departamento de Sistemas Inform’aticos y Computaci’on, Universitat Polit’ecnica de Val’encia]. 10.1.1.1031.2330

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