Brain Tumor Classification Using Hybrid Single Image Super-Resolution Technique With ResNext101_32× 8d and VGG19 Pre-Trained Models-Reference-Cited by-同舟云学术

Brain Tumor Classification Using Hybrid Single Image Super-Resolution Technique With ResNext101_32× 8d and VGG19 Pre-Trained Models

Author:

Mohsen Saeed¹^ORCID,Ali Anas M.²^ORCID,El-Rabaie El-Sayed M.³,ElKaseer Ahmed⁴^ORCID,Scholz Steffen G.⁴^ORCID,Hassan Ashraf Mohamed Ali⁵

Affiliation:

1. Department of Electronics and Communications Engineering, Al-Madinah Higher Institute for Engineering and Technology, Giza, Egypt

2. Robotics and Internet of Things, Prince Sultan University, Riyadh, Saudi Arabia

3. Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt

4. Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany

5. Department of Electronics and Communications Engineering, October High Institute for Engineering and Technology, 6th of October City, Egypt

Funder

Karlsruhe Nano Micro Facility

Helmholtz Research Infrastructure at Karlsruhe Institute of Technology

Helmholtz Research Programme MSE (Materials Systems Engineering) at KIT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference52 articles.

3. EfficientNet: Rethinking model scaling for convolutional neural networks;tan;Proc 36th Int Conf Mach Learn Mach Learn Res,2019

Cited by 1 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. Brain Tumor Classification Through MR Imaging: A Comparative Analysis;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024