2022
DOI: 10.1016/j.imu.2022.100916
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Transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images

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Cited by 75 publications
(36 citation statements)
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References 56 publications
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“…Belal Hossain et al [ 16 ] developed a transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images. In this paper, the authors present a method for how to identify the presence of COVID-19 in X-ray images, using transfer learning (TL) on a ResNet50 model.…”
Section: State-of-the-art Methodsmentioning
confidence: 99%
“…Belal Hossain et al [ 16 ] developed a transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images. In this paper, the authors present a method for how to identify the presence of COVID-19 in X-ray images, using transfer learning (TL) on a ResNet50 model.…”
Section: State-of-the-art Methodsmentioning
confidence: 99%
“…Overview of the Proposed Method. As reported in References [19] and [20], the ResNet50 model can be used as a useful and powerful tool for many biomedical applications, such as the detection of COVID-19 from chest X-ray images and the diagnosis in 12-lead electrocardiogram. In this article, a fine-tuning ResNet50 model was performed and tested for the automatic detection of superficial cracks in the cracked tooth.…”
Section: Methodsmentioning
confidence: 99%
“…The development of CNN has altered how image classification issues are handled [18]. MobileNetV2 [19], ResNet50 [20], DenseNet169 [21], and InceptionResNetV2 [22] are four kinds of CNN architecture employed in this paper to identify diseases in Robusta coffee leaves. Following is a concise explanation of the CNN architecture used in this research.…”
Section: Model Convolutional Neural Networkmentioning
confidence: 99%