Hybridized classification approach for magnetic resonance brain images using gray wolf optimizer and support vector machine-Reference-Cited by-同舟云学术

Hybridized classification approach for magnetic resonance brain images using gray wolf optimizer and support vector machine

Published:2019-07-01 Issue:19 Volume:78 Page:27983-28002
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Ahmed Heba M.,Youssef Bayumy A. B.,Elkorany Ahmed S.^ORCID,Elsharkawy Zeinab F.,Saleeb Adel A.,El-Samie Fathi Abd

Publisher

Springer Science and Business Media LLC

Subject

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

Link

http://link.springer.com/content/pdf/10.1007/s11042-019-07876-8.pdf

Reference45 articles.

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3. Ahmed HM, Youssef BAB, Elkorany AS, Saleeb AA, Abd El-Samie F (2018) Hybrid gray wolf optimizer–artificial neural network classification approach for magnetic resonance brain images. Appl Opt 57(7):B25–B31

4. Ahmmed R, Swakshar AS, Hossain F, Rafiq A (2017) Classification of tumors and it stages in brain MRI using support vector machine and artificial neural network. IEEE Int Conf Electric Comput Commun Eng (ECCE), Cox's Bazar, Bangladesh 16-18:229–234

5. Amin J, Sharif M, Yasmin M, Fernandes SL (2017) A distinctive approach in brain tumor detection and classification using MRI. Pattern Recogn Lett

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