AutoCovNet: Unsupervised feature learning using autoencoder and feature merging for detection of COVID-19 from chest X-ray images

With the onset of the COVID-19 pandemic, the automated diagnosis has become one of the most trending topics of research for faster mass screening. Deep learning-based approaches have been established as the most promising methods in this regard. However, the limitation of the labeled data is the mai...

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Detalles Bibliográficos
Autores principales: Rashid, Nayeeb, Hossain, Md Adnan Faisal, Ali, Mohammad, Islam Sukanya, Mumtahina, Mahmud, Tanvir, Fattah, Shaikh Anowarul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. 2021
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526490/
https://www.ncbi.nlm.nih.gov/pubmed/34690398
http://dx.doi.org/10.1016/j.bbe.2021.09.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526490/
https://www.ncbi.nlm.nih.gov/pubmed/34690398
http://dx.doi.org/10.1016/j.bbe.2021.09.004

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