Federated Learning Using the Particle Swarm Optimization Model for the Early Detection of COVID-19-Reference-Cited by-同舟云学术

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Federated Learning Using the Particle Swarm Optimization Model for the Early Detection of COVID-19

Published:2023-11-26 Issue: Volume: Page:425-436
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Dasaradharami Reddy K.^ORCID,Srivastava Gautam^ORCID,Zhu Yaodong^ORCID,Supriya Y.^ORCID,Yenduri Gokul^ORCID,Victor Nancy^ORCID,Anusha S.^ORCID,Gadekallu Thippa Reddy^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-8132-8_32

Reference32 articles.

1. Agrawal, S., Chowdhuri, A., Sarkar, S., Selvanambi, R., Gadekallu, T.R.: Temporal weighted averaging for asynchronous federated intrusion detection systems. Comput. Intell. Neurosci. 2021, 5844728 (2021)

2. Agrawal, S., et al.: Federated learning for intrusion detection system: concepts, challenges and future directions. Comput. Commun. 195, 346–361 (2022)

3. AlMohimeed, A., Saleh, H., El-Rashidy, N., Saad, R.M., El-Sappagh, S., Mostafa, S.: Diagnosis of Covid-19 using chest X-ray images and disease symptoms based on stacking ensemble deep learning. Diagnostics 13(11), 1968 (2023)

4. Ayan, E., Ünver, H.M.: Diagnosis of pneumonia from chest X-ray images using deep learning. In: 2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT), pp. 1–5. IEEE (2019)

5. Bhapkar, H., Mahalle, P.N., Dey, N., Santosh, K.: Revisited COVID-19 mortality and recovery rates: are we missing recovery time period? J. Med. Syst. 44(12), 1–5 (2020)

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