COVID-19 continues to have catastrophic effects on the lives of human beings throughout the world. To combat this disease it is necessary to screen the affected patients in a fast and inexpensive way. One of the most viable steps towards achieving this goal is through radiological examination, Chest X-Ray being the most easily available and least expensive option. In this paper, we have proposed a Deep Convolutional Neural Network-based solution which can detect the COVID-19 +ve patients using chest X-Ray images. Multiple state-of-the-art CNN models—DenseNet201, Resnet50V2 and Inceptionv3, have been adopted in the proposed work. They have been trained individually to make independent predictions. Then the models are combined, using a new method of weighted average ensembling technique, to predict a class value. To test the efficacy of the solution we have used publicly available chest X-ray images of COVID +ve and –ve cases. 538 images of COVID +ve patients and 468 images of COVID –ve patients have been divided into training, test and validation sets. The proposed approach gave a classification accuracy of 91.62% which is higher than the state-of-the-art CNN models as well the compared benchmark algorithm. We have developed a GUI-based application for public use. This application can be used on any computer by any medical personnel to detect COVID +ve patients using Chest X-Ray images within a few seconds.

COVID-19继续对全世界人类的生命造成灾难性影响。为了对抗这种疾病，有必要以快速且廉价的方式筛查患病患者。实现此目标最可行的步骤之一是通过放射学检查，胸部X射线检查是最容易获得且最便宜的选择。在本文中，我们提出了一种基于深度卷积神经网络的解决方案，该解决方案可以使用胸部X射线图像检测COVID-19 + ve患者。提议的工作采用了多个最新的CNN模型-DensNet201，Resnet50V2和Inceptionv3。他们已经接受了单独培训，可以做出独立的预测。然后，使用一种新的加权平均集合技术对模型进行组合，以预测类别值。为了测试该解决方案的有效性，我们使用了公开的COVID + ve和–ve病例的胸部X射线图像。将538张COVID + ve患者的图像和468张COVID –ve患者的图像分为训练集，测试集和验证集。所提出的方法给出了91.62％的分类精度，这比最新的CNN模型以及比较的基准算法要高。我们已经开发了基于GUI的应用程序以供公众使用。任何医务人员都可以在任何计算机上使用此应用程序，以在几秒钟内使用胸部X射线图像检测COVID + ve患者。所提出的方法给出了91.62％的分类精度，这比最新的CNN模型以及比较的基准算法要高。我们已经开发了基于GUI的应用程序以供公众使用。任何医务人员都可以在任何计算机上使用此应用程序，以在几秒钟内使用胸部X射线图像检测COVID + ve患者。所提出的方法给出了91.62％的分类精度，这比最新的CNN模型以及比较的基准算法要高。我们已经开发了基于GUI的应用程序以供公众使用。任何医务人员都可以在任何计算机上使用此应用程序，以在几秒钟内使用胸部X射线图像检测COVID + ve患者。