Detection Covid-19 Based on Chest X-ray Images Using Convolution Neural Networks | ||
| IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING | ||
| Article 4, Volume 22, Issue 1, March 2022, Pages 34-42 PDF (1.05 M) | ||
| DOI: https://doi.org/10.33103/uot.ijccce.22.1.4 | ||
| Authors | ||
| sufyan zaben; Akbas Ezaldeen Ali | ||
| Computer Science Department, University of Technology, Baghdad, Iraq | ||
| Abstract | ||
| Covid-19 is a deadly virus that has spread worldwide, causing millions of deaths. Chest X-ray is one of the most common methods of diagnosing the infection of Covid - 19. Therefore, this paper has presented an efficient method to detect Covid-19 through X-rays of the chest area through a Neural convolution network (CNN). the proposed system has used a convolution neural network to classify the extracted features. Since CNN needs a set of data defined for training and testing, the proposed method used a public dataset of 350 pneumonia x-ray images, 300 viral images, and 350 normal images for evaluation. Besides, the proposed work achieved a satisfactory accuracy of 95% based on the X-ray image. | ||
| Keywords | ||
| COVID-19; chest X-ray; Neural convolution network; Deep learning | ||
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