7 Moreover, the COVID-19 disease may cause severe problems for the patients having difficulty in breathing, sudden cardiac arrest, multiorgan failure, and pneumonia. 6 The biological composition of COVID-19 consists of positive-sense single-stranded RNA-type, and it is more complicated to diagnose the COVID-19 due to its mutating power. 5 The widespread occurrence of COVID-19 has been of greater trouble to the world health organization since no effectual treatment has been found. 4 Coronavirus affects animals, but the virus can be transmitted to humans due to its zoonotic nature. In the first month of 2020, COVID-19 expands all over the world through transmission from human to human. 3 It was detected in November 2019 in Wuhan city. Moreover, the COVID-19 outbreak is a respiratory infection that is caused by serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2). 1 Hence, it is very important to identifythe COVID-19 disease 2 as fast as possible for controlling the virus spread. For this case, it has very overwhelming effects in numerous fields across the world. Furthermore, the proposed technique achieved effective performance in terms of True Positive Rate (TPR), True Negative Rate (TNR), and accuracy with the maximum values of 0.933%, 0.890%, and 0.919%.Ĭoronavirus is an outbreak that transmits very quickly from person to person. Finally, the COVID-19 detection is performed using the proposed IWS-based DeepNet. For feature extraction, the proposed MLFT is newly developed by considering various texture features for extracting the best features. The noises present in the input chest x-ray (CXR) image are discarded using Region of Interest (RoI) extraction by adaptive thresholding technique. The IWS is devised by incorporating the Improved Invasive Weed Optimization (IIWO) and Sea Lion Optimization (SLnO), respectively. The developed IWS-based DeepNet is developed for detecting COVID-19to optimize the structure of the Deep Convolutional Neural Network (Deep CNN). Therefore, a robust and effective multi-local texture features (MLTF)-based feature extraction approach and Improved Weed Sea-based DeepNet (IWS-based DeepNet) approach is proposed for detecting the COVID-19 at an earlier stage. Various methods are developed for detecting the COVID-19, but the process of diagnosing this problem from radiology and radiography images is one of the effective procedures for diagnosing the affected patients. The corona virus disease 2019 (COVID-19) pandemic has a severe influence on population health all over the world.

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