COVID-19 Classification from X-Ray Images: An Approach to Implement Federated Learning on Decentralized Dataset-Reference-Cited by-同舟云学术

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COVID-19 Classification from X-Ray Images: An Approach to Implement Federated Learning on Decentralized Dataset

Published:2023 Issue:2 Volume:75 Page:3883-3901
ISSN:1546-2226
Container-title:Computers, Materials & Continua
language:en
Short-container-title:

Author:

Akbar Siddique Ali,M. Umar Talha S.,Aamir M.,D. Algarni Abeer,F. Soliman Naglaa,El-Shafai Walid

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanics of Materials,Modeling and Simulation,Biomaterials

Link

https://www.techscience.com/cmc/v75n2/52121/pdf

Reference45 articles.

1. Extensive COVID-19 X-ray and CT chest images dataset;El-Shafai;Mendeley Data,2020

2. Efficient deep-learning-based autoencoder denoising approach for medical image diagnosis;El-Shafai;Computers, Materials and Continua,2022

3. Automated COVID-19 detection based on single-image super-resolution and CNN models;El-Shafai;Computers, Materials and Continua,2021

4. Spatial impressions monitoring during COVID-19 pandemic using machine learning techniques;Noor;Computers,2022

5. Code-free deep learning for multi-modality medical image classification;Korot;Nature Machine Intelligence,2021

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3. Optimizing Tumor Classification Through Transfer Learning and Particle Swarm Optimization-Driven Feature Extraction;IEEE Access;2024

4. Performance evaluation of federated learning algorithms using breast cancer dataset;Federated Learning for Digital Healthcare Systems;2024

5. Ensemble learning for multi-class COVID-19 detection from big data;PLOS ONE;2023-10-11

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