The main objective is to detect the covid-19 virus using a deep learning algorithm. The DenseNet-121 technique is a deep learning-based method for effectively detecting pictures. This study demonstrates that using convolutional neural networks, it is able to predict covid-19 patients based on a CT scan. For patients with covid-19, chest radiography images have been found to be an effective screening technique. To speed up and improve the detection of covid-19 in radiological imaging, many AI-based approaches have been developed. Finally, the two-class image categorization as Covid-19 and Non Covid-19 was performed using the provided deep learning model. The destructive effects of Coronavirus 2019 have recently had an influence on public health and human lives. By establishing a chaotic healthcare system that is immensely more harmful, this devastating result has destroyed the human experience. COVID-19's highly contagious qualities throughout human societies have resulted in a global pandemic. Due to the lack of a COVID-19 vaccine that can only control rather than cure the infection, early and accurate virus identification can be a promising strategy for detecting and preventing the infection from spreading (e.g., by isolating the patients). This circumstance suggests that the auxiliary COVID-19 detection technique should be improved.



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