COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios
Abstract
Highlights • COVID-19 identification in chest X-ray using multi-class and hierarchical learners.• Using a database that reflects a real world scenario with its natural imbalance.• Exploring the textural content from the chest X-ray images with pneumonia.• Evaluating handcrafted and learned features to investigate its complementarities.
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