Highlights Proposed automatic COVID screening (ACoS) system for detection of infected patients. Random image augmentation is applied to incorporate the variability in the images. Applied hierarchical (two phase) classification to segregate three classes. Majority vote based classifier ensemble is used to combine model’s prediction. Proposed method show promising potential to detect nCOVID-19 infected patients.

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