… An early-stage detection of COVID-19 is crucial for the containment of the … this study, a
transfer learning–based COVID-19 screening technique is proposed. The motivation of this study …

… using deep ensemble neural network using transfer learning by fine-tuning the hyper-parameters.
These deep learning models … features with the use of transfer learning. The proposed …

… In this study, we propose an ensemble model for the detection of diabetic retinopathy (DR)
illness that is driven by transfer learning. Due to diabetes, the DR is a problem that affects the …

… learning model is further enhanced by transfer learning and the accuracy of the blade defect
recognition is improved by using the random forest-based ensemble learning … its application …

… images. Therefore, in this article, we propose an Ensembled Transfer Learning (ETL) framework
… images. First of all, we have developed Inception-V3, Xception, VGG-16, and Resnet-50 …

… methodology based on an ensemble of deep transfer learning for the detection of COVID-19. …
years have focused on the application of deep transfer learning in a wide range of medical …

… images’ dimensions are not the same. However, the deep neural network architectures utilized
in this study as part of transfer learning expect all the images … of the image (width x height …

… Although “ensembling” is a phrase that is frequently used in ML, we implemented this
mechanism in the area of neural networks. In further detail, we outline many effective strategies to …

… ensemble approach based on the transfer learning of five different neural network architectures.
… Correct implementation of such tasks may require the use of additional eHealth data …

… but it may also be implemented and used for medical … -based ensemble works particularly
well when assigning weights to the predictions for reaching an ultimate decision on an image's …