CovidDWNet

Feature reuse residual block architecture-(a) and depthwise dilated convolutions architecture-(b), which constitute the basic structure of the proposed architecture

Performance results of the proposed architecture in binary and multiple classes

ROC analysis of the proposed model.

From CovidDWNet architecture using Grad-CAM resulting sample heatmaps and Covid-19 visuals

Updated version and Code metadata

https://doi.org/10.24433/CO.2183919.v1

Citation and More Information:

Celik, G. (2023). Detection of Covid-19 and other pneumonia cases from CT and X-ray chest images using deep learning based on feature reuse residual block and depthwise dilated convolutions neural network. Applied Soft Computing, 133, 109906. https://doi.org/10.1016/j.asoc.2022.109906