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A novel unsupervised approach based on the hidden features of Deep Denoising Autoencoders for COVID-19 disease detection.
Expert Syst Appl. 2022 Apr 15;192:116366. doi: 10.1016/j.eswa.2021.116366. Epub 2021 Dec 16.
Expert Syst Appl. 2022.
PMID: 34937995
Free PMC article.
How much BiGAN and CycleGAN-learned hidden features are effective for COVID-19 detection from CT images? A comparative study.
Sarv Ahrabi S, Momenzadeh A, Baccarelli E, Scarpiniti M, Piazzo L.
Sarv Ahrabi S, et al. Among authors: baccarelli e.
J Supercomput. 2023;79(3):2850-2881. doi: 10.1007/s11227-022-04775-y. Epub 2022 Aug 26.
J Supercomput. 2023.
PMID: 36042937
Free PMC article.
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Twinned Residual Auto-Encoder (TRAE)-A new DL architecture for denoising super-resolution and task-aware feature learning from COVID-19 CT images.
Baccarelli E, Scarpiniti M, Momenzadeh A.
Baccarelli E, et al.
Expert Syst Appl. 2023 Sep 1;225:120104. doi: 10.1016/j.eswa.2023.120104. Epub 2023 Apr 16.
Expert Syst Appl. 2023.
PMID: 37090446
Free PMC article.
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Exploiting probability density function of deep convolutional autoencoders' latent space for reliable COVID-19 detection on CT scans.
Sarv Ahrabi S, Piazzo L, Momenzadeh A, Scarpiniti M, Baccarelli E.
Sarv Ahrabi S, et al. Among authors: baccarelli e.
J Supercomput. 2022;78(9):12024-12045. doi: 10.1007/s11227-022-04349-y. Epub 2022 Feb 24.
J Supercomput. 2022.
PMID: 35228777
Free PMC article.
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