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In recent months the world has been surprised by the rapid advance ofCOVID-19. In order to face this disease and minimize its socio-economicimpacts, in addition to surveillance and treatment, diagnosis is a crucialprocedure. However, the realization of this is hampered by the delay and thelimited access to laboratory tests, demanding new strategies to carry out casetriage. In this scenario, deep learning models are being proposed as a possibleoption to assist the diagnostic process based on chest X-ray and computedtomography images. Therefore, this research aims to automate the process ofdetecting COVID-19 cases from chest images, using convolutional neural networks(CNN) through deep learning techniques. The results can contribute to expandaccess to other forms of detection of COVID-19 and to speed up the process ofidentifying this disease. All databases used, the codes built, and the resultsobtained from the models' training are available for open access. This actionfacilitates the involvement of other researchers in enhancing these modelssince this can contribute to the improvement of results and, consequently, theprogress in confronting COVID-19.

Automatic Detection of COVID-19 Cases on X-ray images Using Convolutional Neural Networks