Abstract
In this paper, ResNet a Convolutional Neural Network for detecting and diagnosing the lung disease Covid-19 pneumonia infection automatically. For identifying, Chest X-rays are widely used for diagnosis of pneumonia disease which affects the lungs. This paper provides an approach to detect and diagnose Covid-19 pneumonia and classify the chest X-ray images into two classes either Covid-19 pneumonia or normal utilizing CNN. This is done by training the CNN to differentiate between the normal and pneumonia chest X-ray images using a deep learning platform Pytorch. Image preprocessing technique has been applied in order to enhance the image accuracy. Python and OpenCV have been used.
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This article has been retracted by IOP Publishing following an allegation that this article may contain tortured phrases [1].
IOP Publishing has investigated and agrees the article contains a number of nonsensical phrases that feature throughout the paper, masking overlap with previously published work [2], to the extent that the article makes very little sense. This casts serious doubt over the legitimacy of the article and/or expertise of the authors in this topic.
IOP Publishing wishes to credit PubPeer commenters [3] for bringing the issue to our attention.
The authors agree to this retraction.
[1] Cabanac G, Labbe C, Magazinov A, 2021, arXiv:2107.06751v1
[2] Angeline R, Mrithika, M., Raman, A., Warrier, P. 2020, Pneumonia Detection and Classification Using Chest X-Ray Images with Convolutional Neural Network. In: Smys, S., Iliyasu, A.M., Bestak, R., Shi, F. (eds) New Trends in Computational Vision and Bio-inspired Computing. ICCVBIC 2018. Springer
[3] https://pubpeer.com/publications/5CE53DABC125D116FC6B848CA1837B