An Ensemble Deep Learning Model for Detection Covid-19 from CT Scan Images
محورهای موضوعی : مجله بین المللی ریاضیات صنعتی
Habib Izadkhah
1
(
Department of Computer Science, Faculty of Mathematics, Statistics, and Computer Scence,University of Tabriz, Tabriz, Iran
)
کلید واژه: Deep Learning, Convolutional Neural Network, CT Scan, Covid-19, Transfer Learning, Ensemble Methods.,
چکیده مقاله :
Diagnosis of covid-19 using deep learning on CT scan images can play an important role in helping doctors. In this paper, by combining EfficientNet-B2 and vision transformers (V iT − 1 − 32) neural networks a new deep transfer learning is proposed. For evaluation, con-fusion matrix, precision, accuracy, recall, and F1 score are used. The experimental results are 0.9838 for validation accuracy, 0.9667 for test accuracy, and 0.9839 for accuracy.
Diagnosis of covid-19 using deep learning on CT scan images can play an important role in helping doctors. In this paper, by combining EfficientNet-B2 and vision transformers (V iT − 1 − 32) neural networks a new deep transfer learning is proposed. For evaluation, con-fusion matrix, precision, accuracy, recall, and F1 score are used. The experimental results are 0.9838 for validation accuracy, 0.9667 for test accuracy, and 0.9839 for accuracy.
.
