… this study, the transfer learning technique was applied using … CNNs employed for automatic
detection was created. Table 2 … of classification function and transfer learning criteria. The fine…

… Since few images of patients with COVID-19 are publicly available, we apply the concept of
transfer learning for this task. We use different architectures of convolutional neural networks …

… in the chest radiograms of patients infected with COVID-19. Inspired by earlier works, we
study the application of deep learning models to detect COVID-19 patients from their chest …

… of COVID-19 pandemic is a lengthy clinical testing time. The imaging tool, such as Chest
X-ray (… CAD system for the detection of COVID-19 samples from healthy and pneumonia cases …

… research in relation to transfer learning-based diagnostics of COVID-19 using chest X-rays …
applied to detect COVID-19. Public datasets containing COVID-19 X-ray images of infected …

… using transfer learning on the COVID-19 dataset that we have created. The results of this
section can be used as a … of different algorithms having the sole purpose to detect COVID-19. …

… used for COVID-19, including X-Rays and CT-scans. This study focuses on detecting COVID-19
… We pursue two types of problems: binary classification (COVID-19 and No COVID-19) …

… transfer learning for coronavirus detection in chest X-ray images is presented. The lack of
datasets for COVID-19 especially in chest … motivation of this scientific study. The main idea is to …

… architectures for detecting the symptoms of COVID-19 in chest X-ray images. These models
were trained over 6087 images. Inception-ResNetV2 provided the classification accuracy of …

… of COVID-19, we propose a fully automated deep learning-based method for the detection
of COVID-19 … The proposed method was based on a transfer learning approach using dense …