ConvCoroNet: a deep convolutional neural network optimized with iterative thresholding algorithm for Covid-19 detection using chest X-ray images-Reference-Cited by-同舟云学术

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ConvCoroNet: a deep convolutional neural network optimized with iterative thresholding algorithm for Covid-19 detection using chest X-ray images

Published:2023-06-24 Issue: Volume: Page:1-14
ISSN:0739-1102
Container-title:Journal of Biomolecular Structure and Dynamics
language:en
Short-container-title:Journal of Biomolecular Structure and Dynamics

Author:

Merrouchi M.¹,Benyoussef Y.²,Skittou M.¹,Atifi K.¹,Gadi T.¹

Affiliation:

1. Faculty of Science and Technology, Hassan First, Settat, Morocco

2. National School of Applied Sciences, Hassan First, Berrechid, Morocco

Publisher

Informa UK Limited

Subject

Molecular Biology,General Medicine,Structural Biology

Link

https://www.tandfonline.com/doi/pdf/10.1080/07391102.2023.2227726

Reference48 articles.

1. A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images

2. Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks

3. Detection of COVID ‐19 from chest X‐ray images: Boosting the performance with convolutional neural network and transfer learning

4. Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images

5. BIMCV-COVID19 – BIMCV. (n.d). https://bimcv.cipf.es/bimcv-projects/bimcv-covid19/#1590858128006-9e640421-6711

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