An Ensemble Deep Learning Model for Detection Covid-19 from CT Scan Images

محورهای موضوعی : مجله بین المللی ریاضیات صنعتی

Habib Izadkhah ¹

1 - Department of Computer Science, Faculty of Mathematics, Statistics, and Computer Scence,University of Tabriz, Tabriz, Iran

تاریخ دریافت : 1401/01/15 تاریخ پذیرش : 1401/05/22 تاریخ انتشار : 1402/12/06

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.

چکیده انگلیسی:

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.