ABSTRACT
The COVID-19 outbreak has been causing immense damage to global health and has put the world under tremendous pressure since early 2020. The World Health Organization (WHO) has declared in March 2020 the novel coronavirus outbreak as a global pandemic. Testing of infected patients and early recognition of positive cases is considered a critical step in the fight against COVID-19 to avoid further spreading of this epidemic. As there are no fast and accurate tools available till now for the detection of COVID-19 positive cases, the need for supporting diagnostic tools has increased. Any technological method that can provide rapid and accurate detection will be very useful to medical professionals. However, there are several methods to detect COVID-19 positive cases that are typically performed based on chest X-ray images that contain relevant information about the COVID-19 virus. This paper goal is to introduce a Detectron2 and Faster R-CNN to diagnose COVID-19 automatically from X-ray images. In addition, this study could support non-radiologists with better localization of the disease by visual bounding box. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.