COVID-19 detection using machine learning and fusion-based deep learning models

The COVID-19 pandemic has been one of the most challenging crises attacking world in last three years. Many systems have introduced field detection.
 In this research, machine learning and deep models for detection with a probability presence are proposed. scenario, dataset is split into 70% training 30% testing, segmentation process applied to CT images order get lung ROI only. features then extracted using Gabor-Wavelet deep-based features. SVM classifier trained evaluated. For model, fed model without feature extraction, different DL (CNN, GoogleNet, ResNet50) Other scenarios proposed which fused, also fused better performance. experiments show that best fusion by system achieved 96.4156%, 96.1905%, 96.1905% accuracy, precision, recall, respectively.